# LABLOOP W04 — batchlens first release: full learning notebook

Prepared 2026-09-23 for Peter Ciancaglini. This is a study and execution guide; it does not record that you completed the work. Keep your existing notes, commitments, progress and evidence. Write actual results in the existing evidence register, not into the illustrative examples below.

[Original weekly brief](./specs.md) · [Commitment](./commitment.md) · [Evidence](./evidence.md) · [Review](./review.md) · [Existing read/watch materials](./materials.md) · [Notebook index and export guide](../../NOTEBOOKS.md) · [NotebookLM upload text](./notebooklm.txt)

[Previous notebook](../week-03-statistical-batch-monitoring/learning-notebook.md) · [Next notebook](../week-05-fermlit-corpus-and-schema/learning-notebook.md)

## 1. The week in plain language: what, why and where it leads

A release is a stable, citable version of a working instrument. This week turns your monitoring prototype into something another person can run and challenge. The main result is a measured description of behavior on held-out batches, including errors. The release also needs instructions, versions and citation information. A DOI identifies an archived object; it does not prove scientific correctness or peer review.

**Your systems, software and AI connection.** Your software release discipline becomes research reproducibility. A scientist needs not just a package installation but the precise path from source data to a headline number. This gate supplies the first public proof for later reports, papers, technical interviews and eventual software review.

**Dependency map from the existing programme.**

- ← **From:** weeks 1-3 (simulator, tidy data, alarms).
- → **Feeds:** week 8 (technical report cites v0.1), week 12 and 17 (batch-wise CV is the backbone of the learning curves), week 36 (JOSS needs a clean release history).
- ⟳ **Returns in:** every release: v0.2 (wk 8), v0.3 (wk 17).

**Gate and proof required by the current weekly specification.**

This is Gate 04: **Public and reproducible**.

Required proof: batchlens v0.1 public, measured headline, reproducible report, actual DOI.

Reputation interpretation: L1; L2 when citable. Record target, forecast, actual date and evidence link. The original gate stays incomplete until the required external proof exists.

The milestones are targets, not predictions of success. A prepared notebook, generated visual, course completion or draft paper is not a substitute for the required evidence. Your final profile should connect a clear scientific question to working software, trustworthy data, measured comparisons, documented limitations and your own contribution.

## 2. Before starting: locate inputs and repair only the needed foundations

- [Week 03](../week-03-statistical-batch-monitoring/specs.md): inspect its actual evidence and review; source/code artifacts must exist before the dependent task begins.

1. Open the existing commitment and previous review/evidence. Identify which required inputs are present, missing or stale. A folder name does not prove its project is complete.
2. Locate the canonical code/data repository and note its current version. The coordinating files named below live in this weekly folder; implementations and measured outputs belong in the canonical project, linked from evidence.md.
3. Read the plain-language explanation and worked example before selecting sources. Try the small calculation or reasoning exercise on paper. Mark any unfamiliar symbol or word.
4. Use the relevant refresher below inside your allocated study time. Say the idea aloud in your own words, work one example and connect it to a named output. Park material that does not unblock this week.
5. Write the next physical action in TODAY.md and start the allocated block. If a human, dataset or external event is missing, continue independent preparation and mark the dependent task pending.

You have professional experience and are rebuilding dormant foundations; unfamiliar notation is a repairable gap. For each equation, identify the question, read every symbol aloud, attach units, substitute small numbers and only then translate it to code.

## 3. Foundation refreshers you can use without another notebook

### Independent evidence, baselines and leakage

An **observation** is a recorded value; an **independent experimental unit** is the entity whose variation supports your generalization claim. Many timestamps from one batch, fields from one paper, relatives in a protein family or wells from one biological sample are related. Split and analyze at the unit appropriate to the question.

**Training data** fit the model. **Development/validation data** guide choices. **Calibration data** set a threshold or interval under a defined procedure. **Test data** are reserved for the final specified evaluation. These roles may be implemented through carefully designed cross-validation, but their purposes must remain separate. **Leakage** occurs when unavailable information influences a prediction or evaluation—future samples, test-derived scaling, duplicated papers or close sequence relatives can all cause it. [The scikit-learn pitfalls guide](https://scikit-learn.org/stable/common_pitfalls.html) documents preprocessing and leakage traps.

A **baseline** is a simple, relevant reference method. Compare models on the same target, units, observation cutoff and independent groups. Record a split manifest and freeze preprocessing rules before testing. A fixed random seed makes a procedure repeatable; it does not make a bad split valid. When test errors guide a revision, label that test as reused/development and reserve new evidence for the next independent claim. A negative result is still a completed, useful experiment.

### What a number does—and does not—establish

An average summarizes observations but hides spread and sample support. Always ask: what was measured, on how many independent units, with what variability? An **effect size** is a difference or association in a meaningful scale, such as an error reduction in g/L. A small p-value does not make the effect large or useful.

A **confidence interval** comes from a procedure intended to cover a population quantity at a stated rate across repeated sampling under its assumptions. A **credible interval** describes uncertainty under a Bayesian model and its prior. A **prediction interval** concerns a future observation, which is different from uncertainty about an average. A bootstrap resamples data to approximate sampling variability; resample independent groups when rows are related. Report which interval you used and how, rather than writing an unlabeled “±”.

Conformal prediction uses a separate calibration procedure to construct prediction sets/intervals. Its usual guarantees depend on assumptions such as exchangeability of calibration and future cases; shifted faults or new protein families may violate them. Read the assumptions in [Angelopoulos and Bates, sections 1–2](https://arxiv.org/abs/2107.07511) before presenting a guarantee. **Identifiability** asks whether the observed data can distinguish parameter values. An optimizer returning a number is not evidence that the parameter is identifiable. Plot failures and uncertainty, and keep “unknown” available as an answer.

### How a professional research claim earns trust

Use a chain you can inspect: **question → source data → method → output → interpretation → limitation**. A claim is a sentence someone could challenge. An artifact is the file, figure, release or record that supports it. Verification explains how you checked the artifact. A screenshot can show a graph existed; code, inputs and commands allow someone to recreate it.

Every experiment needs the question or exploratory label, independent unit, data origin/rights/version/hash, baseline, split, code/config/seed, command, outputs, errors and interpretation. Keep synthetic teaching examples separate from programme results. Every public/career claim also needs your actual contribution and the correct state: prepared, sent/submitted, public, reviewed, accepted or paid/delivered.

Keep evidence in the weekly register with links to canonical project files. A DOI identifies an object; it is not peer review. A contact is not a collaborator; a submission receipt is not acceptance. These distinctions strengthen your profile because a scientist, recruiter or buyer can trust the claims that are supported. Learning evidence is personal too: explain a concept without notes, perform a small calculation, reproduce an output and identify a failure. A prepared notebook does not mean you have completed the week.

## 4. This week’s specific study bridge

Biology B4: metabolism is the network of chemical transformations; distinguish respiration from biochemical fermentation and from industrial use of the word fermentation. AI M4: cross-validation rotates the held-out groups to assess model choices; a final reserved test remains separate. Bootstrap samples approximate variability under a chosen sampling unit. Sketch a batch-wise fold and explain why ten timestamps from one batch are not ten fresh batches.

### Biology/domain assignment retained from the plan

Source unit: B4 · Microbial metabolism and fermentation

Material: *Microbiology* ch. 8 "Microbial Metabolism" (8.1-8.4)

Produce: Notes; one paragraph "what is a fermentation, really"

Understanding check: You can explain aerobic vs anaerobic to a friend

### AI/scientific-method assignment retained from the plan

Source unit: M4 · Validation done right

Material: ISLP ch. 5 (cross-validation, bootstrap)

Produce: Batch-wise CV implemented in batchlens

Understanding check: You can explain leakage across batches

These inherited chapter/lecture lists are resource menus. Select the subsection that answers the named understanding check. Do not add full-course viewing to the 600-minute week. The source/stash section below supplies the existing locators and marks searches as searches.

## 5. Resource stashes: open, study, apply and retain

Open [this week’s resource stash](http://127.0.0.1:5000/learn?stash=LABLOOP-W04%20Notebook) or [the complete weekly deck](http://127.0.0.1:5000/learn?week=4). These addresses work when the local cockpit runs on its default port; use its current address if you changed it. The public source links below also work independently of the cockpit. The weekly stash groups the existing cards; saving a card does not mark it studied.

Use **core** resources first, **run** resources when implementing a specific step, and **deeper** resources only after the critical work fits. Read the stated scope with one question in mind, then produce the note/calculation/artifact before opening another source. Times are inherited estimates, not extra allocations or a promise that every resource fits. Some cards contain an entire course or repository: use only the named topic/exercise.

**Source status.** This catalog preserves the programme’s resources. Direct links are locators, not a claim that all content was freshly inspected. Search links still need an exact source selected. The [source-check log](../../notebooks/source-checks.md) records the targeted checks and corrected FLIP locator; verify mutable versions, access rights, venues, roles and costs when executing. A NotebookLM upload does not automatically import every linked page.

| Card and source | Tier / slot | Scope or task from the existing resource | Time guide |
|---|---|---|---|
| [OpenStax Microbiology, ch. 8 "Microbial Metabolism" — source](https://openstax.org/books/microbiology/pages/8-1-energy-matter-and-enzymes) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-49e6ffc8) | core / Tuesday | 8.1 through 8.4; pay attention to aerobic vs anaerobic | 30 min (estimate) |
| [Sandve G. et al., "Ten Simple Rules for Reproducible Computational Research", PLOS Comp. Biol. 9… — source](https://doi.org/10.1371/journal.pcbi.1003285) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-4b0647fa) | core / Tuesday | All ten rules, they are one page each | 30 min (estimate) |
| [Khan Academy · "Fermentation and anaerobic respiration" — source](https://www.khanacademy.org/science/ap-biology/cellular-energetics/cellular-respiration-ap/a/fermentation-and-anaerobic-respiration) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-b99cf685) | core / Tuesday | Optional explanation of the card’s named concept; use only if the core note is unclear. | 10 min |
| [GitHub Docs, "Referencing and citing content" and "About CITATION files"; format spec at citatio… — source](https://docs.github.com/articles/referencing-and-citing-content) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-93e35337) | core / Wednesday | The Zenodo-integration steps and the minimal CITATION.cff fields | 30 min (estimate) |
| [StatQuest · "Machine Learning Fundamentals: Cross Validation" — source](https://www.youtube.com/watch?v=fSytzGwwBVw) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-94c5e051) | core / Thursday | The sentence "why random k-fold is wrong for batch data" in notes/ml/M4.md | 6 min |
| [StatQuest · "Bootstrapping Main Ideas!!!" — source](https://www.youtube.com/@statquest) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-75d0e45a) | core / Thursday | Nothing; it supports ISLP 5.2 | 9 min |
| [ISLP ch. 5 "Resampling Methods" — source](https://www.statlearning.com/) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-c76a9163) | core / Thursday | 5.1 cross-validation and 5.2 bootstrap; then the ch. 5 lab | 30 min (estimate) |
| [Kapoor S. & Narayanan A., "Leakage and the reproducibility crisis in machine-learning-based scie… — source](https://doi.org/10.1016/j.patter.2023.100804) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-81ec0d11) | core / Thursday | The taxonomy of eight leakage types; identify which one batch-wise CV prevents | 30 min (estimate) |
| [The Turing Way, chapter on "Version control" and "Research compendia" — search; resolve first](https://duckduckgo.com/?q=The+Turing+Way%2C+chapter+on+%22Version+control%22+and+%22Research+compendia%22) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-b36e16ec) | deeper / Saturday · sandbox, optional | The Turing Way, chapter on "Version control" and "Research compendia" | 30 min (estimate) |
| [The Turing Way — book.the-turing-way.org, chapters on "Version control" — source](https://book.the-turing-way.org) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-70ec9025) | deeper / Saturday · sandbox, optional | The Turing Way — book.the-turing-way.org, chapters on "Version control" and "Research compendia". The grown-up version of what you shipped this week | 30 min (estimate) |
| [carpentries-lab/good-enough-practices — source](https://github.com/carpentries-lab/good-enough-practices) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-7b419602) | deeper / Saturday · sandbox, optional | carpentries-lab/good-enough-practices — the hands-on lesson behind week 00's R3 | 30 min (estimate) |
| [Zenodo help — source](https://help.zenodo.org/) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-745d6736) | deeper / Saturday · sandbox, optional | Zenodo help — versioning and GitHub integration, if the DOI badge misbehaves | 30 min (estimate) |
| [JOSS submission guidance — source](https://joss.readthedocs.io/en/latest/submitting.html) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-a638760f) | deeper / Saturday · sandbox, optional | JOSS submission guidance — you submit in week 36, not now. Read it once so that today's release history is already the kind reviewers want | 30 min (estimate) |
| [intro-stat-learning/ISLP_labs — source](https://github.com/intro-stat-learning/ISLP_labs) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-373d343e) | run / Any block this week — the plan names no day | Colab: Ch05-resample-lab.ipynb; then rewrite one cell using GroupKFold with batch as the group | 30 min |
| [scikit-learn/scikit-learn — source](https://github.com/scikit-learn/scikit-learn) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-b54b55a4) | run / Any block this week — the plan names no day | User guide "Cross-validation: evaluating estimator performance", section on group-wise splitters; run the visualization example "Visualizing cross-validation behavior" | 30 min |
| [google-research/tuning_playbook — source](https://github.com/google-research/tuning_playbook) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-d679e4ac) | run / Any block this week — the plan names no day | Read only the section on evaluation and "incremental tuning"; one page of habits you will reuse in weeks 8 and 17 | 30 min |
| [drivendataorg/cookiecutter-data-science — source](https://github.com/drivendataorg/cookiecutter-data-science) · [card](http://127.0.0.1:5000/learn?week=4#card-w04-9e8466d2) | run / Any block this week — the plan names no day | Compare your Makefile with its conventions; add make report FAKE=1 | 30 min |

### A bounded way to read a scientist’s paper

Use the founder-paper slot only where scheduled. Select a paper relevant to this week through the existing resources or a verified author profile; record title, authors, year, exact URL and what full text you could access. In 30 minutes: 5 for the question and experimental unit; 10 for one relevant methods passage and figure; 10 for a digest; 5 for three questions. Your digest should say question → method → measured result with N/units → limitation → connection to this week’s artifact. If you only read the abstract, say so and leave inaccessible methods/results unknown. This notebook has not read a future partner paper on your behalf.

## 6. Seven-day runbook: what to do, why and when to stop

Use the original weekly allocation: six 90-minute days plus a 60-minute Sunday, totaling 600 minutes. Reading this notebook, creating study visuals, debugging, calls and evidence recording all consume that same capacity. This is a reference you open section by section, not an additional course to finish before building.

| Day | Budget | Existing target and stopping condition |
|---|---:|---|
| Monday | 90 min | Compute detection delay from fault onset, lead time before harvest, false-alarm rate and undetected fraction on held-out batches. Stop when: Definitions, numerator/denominator, N and interval method accompany each metric. |
| Tuesday | 90 min | *Microbiology* ch. 8 "Microbial Metabolism" (8.1-8.4) Produce: Notes; one paragraph "what is a fermentation, really" |
| Wednesday | 90 min | Prepare README, install instructions, CITATION.cff, license and release metadata with a clean-environment reproduction check. Stop when: Headline results trace to commands and input checksums. Reserve the last 10 minutes for the optional Wednesday note. |
| Thursday | 90 min | ISLP ch. 5 (cross-validation, bootstrap) Select material/exercise that fits 60 minutes; use the last 30 for the founder paper. |
| Friday | 90 min | Package batchlens v0.1 and DOI deposit materials; prepare a bounded review request for the Sumble contact. Stop when: Release is ready; public URL and DOI count only when actually issued. |
| Saturday | 90 min | Resolve the earliest critical spillover or dependency. Prepare any long-form publication draft from existing figures here if needed. Sandbox only after commitments are met. |
| Sunday | 60 min | 20 min build-log draft/publication when authorized; 5 min evidence/checklist; 20 min source-grounded gap review; 15 min next week's six physical actions. |

### Monday challenge — `release-metrics.csv`

**Do these steps in order.**

1. Freeze the alarm policy, split and evaluation command.
2. For each faulty batch record onset, first qualifying alarm, harvest time and whether it was detected.
3. Calculate detection delay=alarm−onset and lead time=harvest−alarm only where those events exist.
4. Count normal batches with any false alarm and all normal batches.
5. Report misses separately.
6. Choose interval methods at the independent-batch level and store numerator, denominator, units and uncertainty alongside each estimate.

**Why this matters.** This output closes the input/question part of the week’s evidence chain. Its acceptance criterion below determines whether the result can support the next milestone.

**Output and acceptance from the specification:** Compute detection delay from fault onset, lead time before harvest, false-alarm rate and undetected fraction on held-out batches. Acceptance: Definitions, numerator/denominator, N and interval method accompany each metric.

**Block allocation:** 2 minutes open the current inputs and write the immediate action; 78 minutes carry out the steps above; 7 minutes check the acceptance criterion and record output paths/errors; 3 minutes write the next action. These sum to 90 minutes. Stop at the limit and record the exact next step rather than silently expanding the week.

**Evidence to retain:** the artifact or pending-state runbook, input/output paths, version/configuration, the check performed, observed result or exact failure, and your interpretation. Put the link in evidence.md. An intended filename is not proof that a measured output exists.


### Wednesday challenge — `release-checklist.md`

**Do these steps in order.**

1. Write a quickstart using an offline sample before the full data path.
2. Record supported environment and dependencies, license, citation metadata, exact input checksums and output location.
3. Run the instructions from a fresh directory/environment that lacks your cached intermediates.
4. Compare the regenerated tables and figures to the release candidate.
5. Fix missing configuration or implicit paths; document any remaining nondeterminism and runtime.

**Why this matters.** This output closes the implementation/measurement part of the week’s evidence chain. Its acceptance criterion below determines whether the result can support the next milestone.

**Output and acceptance from the specification:** Prepare README, install instructions, CITATION.cff, license and release metadata with a clean-environment reproduction check. Acceptance: Headline results trace to commands and input checksums.

**Block allocation:** 2 minutes open the current inputs and write the immediate action; 68 minutes carry out the steps above; 7 minutes check the acceptance criterion and record output paths/errors; 3 minutes write the next action. The remaining 10 minutes are the optional Wednesday note; reclaim them for the critical task if necessary. These sum to 90 minutes. Stop at the limit and record the exact next step rather than silently expanding the week.

**Evidence to retain:** the artifact or pending-state runbook, input/output paths, version/configuration, the check performed, observed result or exact failure, and your interpretation. Put the link in evidence.md. An intended filename is not proof that a measured output exists.


### Friday challenge — `review-request.md`

**Do these steps in order.**

1. Assemble version v0.1, release notes, archive metadata and a small review package.
2. Explain the problem, one command, one result and one failure.
3. Prepare the review request with a narrow ask such as checking the alarm denominator.
4. Record public release and archive DOI only after they exist; keep local package preparation distinct.
5. Finish the gate checklist against the original required proof, not against the number of files written.

**Why this matters.** This output closes the verification/handoff part of the week’s evidence chain. Its acceptance criterion below determines whether the result can support the next milestone.

**Output and acceptance from the specification:** Package batchlens v0.1 and DOI deposit materials; prepare a bounded review request for the Sumble contact. Acceptance: Release is ready; public URL and DOI count only when actually issued.

**Block allocation:** 2 minutes open the current inputs and write the immediate action; 78 minutes carry out the steps above; 7 minutes check the acceptance criterion and record output paths/errors; 3 minutes write the next action. These sum to 90 minutes. Stop at the limit and record the exact next step rather than silently expanding the week.

**Evidence to retain:** the artifact or pending-state runbook, input/output paths, version/configuration, the check performed, observed result or exact failure, and your interpretation. Put the link in evidence.md. An intended filename is not proof that a measured output exists.


### Tuesday — rebuild the domain concept through an output

1. Spend 10 minutes recalling what you know and listing the specific confusing words in the domain assignment above.
2. Spend up to 35 minutes on the relevant source subsection. Pause to define each term using the actual data or artifact, not only an analogy.
3. Spend 30 minutes producing the assigned note, drawing, calculation or bounded exercise. Label invented teaching numbers as synthetic. For applied weeks, use the exercise/decision in the current challenge.
4. Spend 10 minutes explaining what the concept changes in this week’s work. Record the explanation or write five sentences without looking.
5. Spend 5 minutes saving the output and one unresolved question. These 90 minutes include opening/closing rituals. For a source week with no new coursework, apply this rhythm to its named operational material.

### Thursday — connect the model or decision to the domain

Use 5 minutes to recall the concept, 20 for the smallest relevant source section, 25 for one calculation/code application, 5 to explain it without notes and 5 to log the result. Use the remaining 30 for the scheduled founder-paper digest. If the inherited list is longer than the block, park the rest.

Write one bridge sentence: “I use [concept] in [specific artifact] because it prevents or enables [specific behavior].” Then point to the corresponding field, equation, comparison or paragraph. If you cannot locate the connection, return to the smallest worked example rather than opening more resources.

### Saturday — repair the earliest dependency, then prepare study visuals

Start by reading unresolved acceptance items and choose the one that blocks the next milestone. Spend 2 minutes choosing it, 58 minutes fixing or preparing the smallest checkable result, 7 minutes checking the result and 3 minutes recording the handoff. If critical work is complete, use the remaining 20 minutes to import this notebook or prepare the next week’s sources and request one visual. If not, use those 20 minutes on the dependency. Optional sources and polish move to PARKING.md. A visual study aid does not replace the missing artifact.

### Sunday — review and make next week startable

Use 20 minutes to draft a build log from one actual figure, result or failure, with correct publication state; 5 minutes to update evidence and checklist; 20 minutes to attempt the recall questions and review gaps; 15 minutes to write six next physical actions with filenames and needed inputs. Keep the original gate target and record any revised forecast separately. Actual external publishing follows the authorization available in that execution session.

## 7. Worked example, practice and separate answer key

### Worked teaching example

Synthetic release example: 2 of 20 normal batches alarm, so the batch false-alarm fraction is 10%. Of 10 faulty batches, 8 are detected, so the miss fraction is 20%. A detected case with onset at hour 10, alarm at 12 and harvest at 20 has 2-hour delay and 8-hour lead time. None of these invented values belongs in your actual release table.

These are illustrative reasoning examples or explicitly synthetic numbers, not measurements obtained for your research. Recreate the calculation or reasoning before applying it to actual inputs.

### Your exercise — answer before reading the solution

Why would reporting only the mean delay of detected batches mislead a reader? What extra denominator belongs next to it?

Your answer: ____________________

Your connection to `release-metrics.csv`: ____________________

### Answer key

It hides undetected faults. State detected/total faulty batches and the miss fraction; describe the delay distribution conditional on detection. Keep early false alarms separate from genuine post-onset detection under the predetermined rule.

### Five recall questions and grading guide

1. Explain this week’s purpose to a 15-year-old in three sentences. What real scientific or professional decision does it support?
2. Solve the exercise above and explain each assumption or unit, rather than copying the answer.
3. Open `release-metrics.csv` or its preparation instructions. What exact input, action, output and acceptance check make it inspectable?
4. What could make `release-checklist.md` look convincing while still being wrong? Use the week-specific risk below and name the evidence needed to detect it.
5. What does `review-request.md` pass to the next milestone, and which claim remains unsupported until external or measured evidence exists?

Grade each answer 0 (missing/wrong), 1 (correct but vague or needs prompting), or 2 (correct, explained in your own words and tied to a concrete artifact/example). The purpose/bridge supports Q1; the separate key supports Q2; the runbook and contracts support Q3–Q5. Aim for at least 8/10 with no unresolved misconception about provenance, independence, measured versus predicted results or external status. This is a study-readiness check, not permission to pass the research gate. Save your actual score and gaps; this prepared notebook does not assign them.

## 8. Research evidence and professional profile

### What your weekly evidence record should contain

Copy the blank structure below into the existing evidence.md only when working the task. Keep earlier entries. Use actual values or PENDING with a reason; never copy illustrative numbers as results.

| Evidence field | Your actual entry |
|---|---|
| Question/decision and why it matters | PENDING |
| Artifact name, canonical path and version | PENDING |
| Input origin, access date, rights, version/checksum | PENDING |
| Unit of analysis / target / relevant units | PENDING |
| Method, baseline, assumptions and split or decision rule | PENDING |
| Command/config/seed or document review procedure | PENDING |
| Observed output, independent N and uncertainty where relevant | PENDING |
| Check performed, failures and negative findings | PENDING |
| Interpretation and what the evidence does not establish | PENDING |
| Your contribution and model/human/partner contributions | PENDING |
| External event state and dated receipt/link, if applicable | PENDING |
| Next action, owner and dependency | PENDING |

For documentary or commercial work, replace nonapplicable experimental fields with the actual verification (for example, source-to-claim audit or agreed scope/receipt); write “not applicable” with a reason instead of inventing a metric. For experiments, retain raw data, scripts/configs, per-case results and generated figures in the canonical project. Evidence.md is the index, not a substitute for those artifacts.

### Make the skill-to-proof connection

Complete this sentence from real work: “I used [systems/software/AI capability] to answer [scientific/workflow question], implemented [artifact], checked it using [method], observed [result with context], and found [limitation]. My contribution was [specific work].” This becomes an honest portfolio/interview story. A failed experiment with a sound diagnosis is also evidence of research judgment.

The Week 40 profile should let a reader follow your claims to data/code/releases, manuscripts with exact status, independent feedback, collaboration and actual delivery. Keep a brief record now so you do not reconstruct a research history from memory later.

## 9. Completion checklist, misconceptions and recovery

This is Gate 04: **Public and reproducible**.

Required proof: batchlens v0.1 public, measured headline, reproducible report, actual DOI.

Reputation interpretation: L1; L2 when citable. Record target, forecast, actual date and evidence link. The original gate stays incomplete until the required external proof exists.

- [ ] Monday artifact satisfies: Definitions, numerator/denominator, N and interval method accompany each metric.
- [ ] Wednesday artifact satisfies: Headline results trace to commands and input checksums.
- [ ] Friday artifact satisfies: Release is ready; public URL and DOI count only when actually issued.
- [ ] Study pack is prepared; Peter's actual learning/quiz result is recorded separately.
- [ ] Branding and opportunity drafts use supported claims and the correct external-action state.
- [ ] Reproduction or document checks are recorded with file/version references.
- [ ] This week's special gate, if any, has real evidence or remains explicitly pending.
- [ ] Review, root progress/log and the next physical action are updated.

### Notebook study checklist

- [ ] I can describe the week’s question and its connection to my systems/software/AI work.
- [ ] I repaired the specific prerequisite I needed and completed the worked exercise myself.
- [ ] I used the selected stash sources and saved an applied note rather than only a viewing history.
- [ ] Each challenge has the specified output and a recorded acceptance check, or an explicit missing dependency.
- [ ] I retained source versions, units, split/decision rules, failures and limitations where applicable.
- [ ] I can distinguish illustrative, simulated, predicted and measured information in my work.
- [ ] My research/profile claims link to real evidence and use the correct external status.
- [ ] I recorded actual recall performance, next actions and any unmet gate requirement.

### The specific trap to avoid this week

A DOI establishes citability, not peer review. Maintain public development from this release for the later JOSS target.

Apply the root scientific evidence contract: provenance; meaningful independent splits; no future-data leakage; baseline comparison; actual denominators/uncertainty; failed cases; human review where required. State whether data are simulated, public experimental, synthetic or partner-provided.

Keep source gates intact, and log scope/time conflicts in review. Missing people, money, access or results must not be replaced with invented evidence. Reduce optional polish first. A specific essential external dependency stays pending while independent preparation continues.

### Recovery without losing the programme’s meaning

Source-preserving minimum: the release with the DOI.

Operational first step if stalled: open `release-metrics.csv`, write the required inputs and produce the smallest checkable example in ten minutes. If a more urgent missing gate dependency controls the week, use the source minimum above.

If the full week does not fit, use [P14](../../../LABLOOP-Master-Plan-v6.md#part-8--the-prompt-pack-copy-paste-fill-the-brackets): retain one gate-critical deliverable and one directly supporting study exercise; record what is skipped versus moved. Do not mark the original full gate passed merely because the minimum was completed. After a missed week, reforecast from actual evidence and avoid a second unexamined lost week.

If a prerequisite concept is missing, use the first ten minutes to define it and work one tiny example. If hardware or access fails, use the allowed offline/synthetic preparation and label its scope. If a person, public identifier or payment is required, keep that event pending and finish independent work. A smaller preparation result preserves momentum; it does not replace an unmet gate.

## 10. NotebookLM import and visual study kit

1. Create a notebook named **LABLOOP-W04 · batchlens first release**.
2. Upload this week’s `notebooklm.txt` or `learning-notebook.md`, or paste the complete text as a source. Upload one copy, not both. [Google’s source-import guidance](https://support.google.com/notebooklm/answer/16215270?hl=en) documents text/Markdown and pasted-text sources.
3. Add the exact core source pages or permitted PDFs you selected in Section 5 as separate sources. Linked pages and local cockpit stashes are not recursively imported. Inspect what was actually imported; a video may require an available transcript. You do not need all 454 programme cards in one notebook.
4. When you execute the week, add your own notes, permitted code excerpts, results and review as separate clearly named sources. Use “Measured — …” only for actual measurements. Keep sensitive partner/client records within their permitted use.
5. Request one study output at a time using the prompts below; use the available Studio feature or ask chat for the equivalent outline. Interface/features can vary. Inspect units, labels, citations and the separation between planned and achieved work before studying or sharing a generated visual.

### Week-specific visual brief

Create a release evidence ladder: raw batches → frozen scores → event table → metrics with denominators → figure → versioned release → DOI.

### Copy-ready prompts

**Concept map / infographic**

> Using only the sources in LABLOOP-W04, explain “batchlens first release” to an adult software/systems/AI professional rebuilding science foundations after twenty years. Create a release evidence ladder: raw batches → frozen scores → event table → metrics with denominators → figure → versioned release → DOI. Label each arrow with why it exists. Define every technical term at first use. Connect prerequisite → current challenge → evidence → next milestone. Mark targets, synthetic teaching numbers and measured results distinctly. Cite sources; identify missing evidence instead of inventing it.

**Visual lesson / slides**

> Create an eight-panel visual lesson for Week 04: 1 purpose, 2 needed foundations, 3 one worked example with units, 4 Monday challenge, 5 Wednesday challenge, 6 Friday challenge, 7 common failure and verification, 8 evidence checklist and next milestone. Use simple explanations suitable for a 15-year-old without talking down to an experienced professional. Put detailed speaker notes under each panel. Use the exact artifact filenames and acceptance criteria in this notebook.

**Audio or video study script**

> Teach Week 04 as a guided conversation: what, why, when and how. Explain the mathematical/scientific idea in words before notation. Pause for me to answer the exercise without revealing the solution; then walk through it. Connect my software experience to the scientific question. End with a rehearsal of what evidence I must retain, not a claim that I have already completed the work.

**Flashcards and quiz**

> Make twelve cards: four term/meaning/example cards, four how/why steps from the actual challenges, two unit/assumption checks and two evidence/misconception checks. Then ask five open questions one at a time. Grade each 0–2 using the notebook rubric, explain any error, and cite the relevant section. Do not infer my competence from the existence of the notebook.

**Research review rehearsal**

> Act as a careful research reviewer for Week 04. Ask me to defend the question, inputs, independent unit or decision basis, baseline, method, uncertainty, failure cases and scope of the claim. Use only supplied evidence. Distinguish a preparation artifact from a measured result and an external event. Finish with a claim-to-evidence table and the three smallest actions needed to close real gaps.

## 11. Source and ownership notes

This notebook adds explanation and runbooks to the existing plan. The [weekly specification](./specs.md), [programme decisions](../../DECISIONS.md) and [gates](../../GATES.md) retain authority over sequence, scope and acceptance. The [v6 master](../../../LABLOOP-Master-Plan-v6.md) supplies the dependency map and inherited resource cards; the [source catalog](../../SOURCES.md) records their history. The teaching examples and explanatory bridge are preparation material, not executed findings.

Existing files and learning progress remain separate. Dates stay relative until you choose actual commitments. Peter owns learning, personal claims, scientific responsibility and external relationships; independent humans own their actual annotation/review contributions and partner laboratories own their laboratory execution. This notebook prepares the steps; it does not publish, contact, spend, submit or perform the programme on your behalf.
