# LABLOOP W06 — human gold standard: 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) · [Notebook index and export guide](../../NOTEBOOKS.md) · [NotebookLM upload text](./notebooklm.txt)

[Previous notebook](../week-05-fermlit-corpus-and-schema/learning-notebook.md) · [Next notebook](../week-07-measured-extraction-agent/learning-notebook.md)

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

A gold standard is a carefully checked reference against which the extraction system can be evaluated. It is made by humans applying explicit rules to source material. The value comes from the traceable reasoning and independence, not from calling the file “gold.” This week may expose unclear field definitions or papers that need more time than expected. Those are useful findings about the task.

**Your systems, software and AI connection.** Annotation resembles writing a specification with concrete examples and edge cases. Your quality-engineering habits help, but biological ambiguity requires reading context and documenting uncertainty. Independent human overlap enables the Week 10 agreement analysis and gives Paper 1 a defensible evaluation reference.

**Dependency map from the existing programme.**

- ← **From:** week 5 schema and corpus.
- → **Feeds:** week 7 (the agent is scored against these 50), week 10 (kappa with the second annotator), week 14 (Paper 1 Methods: "Gold standard"), week 34 (labdocs uses the same method with 60 Q&A).
- ⟳ **Returns in:** every evaluation you will ever sell. The gold-set habit is your professional signature.

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

This is an enabling week. Its deliverables feed the next scheduled gate: 8. Complete the acceptance checklist below; do not promote reputation from a draft.

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 05](../week-05-fermlit-corpus-and-schema/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

### From papers to trustworthy experimental records

A paper is a document; an experiment is a specific tested condition or comparison; a measurement is a value associated with that experiment. They require different identifiers. **Provenance** is the trail from a stored value to the document/version, paragraph, sentence or table cell that supports it. Preserve that trail even after normalization.

Missingness has several causes. “Not reported” means the source was inspected and did not provide the field under your rules. “Not extracted” means the pipeline failed or omitted it. “Inaccessible” means you could not inspect the required source. Collapsing them into a blank cell can create a false scientific conclusion about reporting quality. An LLM’s confident answer is not source evidence.

Annotation guidelines make interpretation rules explicit. Independent annotators apply the rules separately; agreement is measured before **adjudication**, the later process of resolving differences. A gold set is a checked reference with known limitations, not an infallible oracle. Corpus selection, annotation coverage and scoring choices all belong in Paper 1’s methods. Read a paper as question → experimental unit → method → observed result → limitation; record an abstract-only access limitation when full methods are unavailable.

### Probability and evaluation without hidden arithmetic

A probability expresses uncertainty about an event under a model or data-generating process. A frequency needs a denominator: 8 successful cases out of 10 is 0.8, but ten related observations do not become ten independent experiments. Conditional probability means “among cases where this condition holds.” Do not swap the condition: the probability of an alarm given a fault is different from the probability of a fault given an alarm.

Bayesian updating combines a prior assumption with the likelihood of observations to obtain a posterior. In a teaching coin model, a uniform Beta(1,1) prior and three heads/one tail give Beta(4,2), whose mean is 4/6. The observations change the belief without eliminating uncertainty. Real data need a defensible likelihood and prior, not just this convenient formula.

For extraction, **precision**=correct extracted items/all extracted items; **recall**=correct extracted items/all reference items. **F1** balances the two: 2TP/(2TP+FP+FN). TP means true positive, FP false positive, FN false negative. Define what “correct item” means for each field, including units, numeric tolerance and source support. Specify behavior when a denominator is zero. A single overall score can conceal a weak field, so show field-level counts.

### 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 B6: an engineered strain has deliberate genetic changes; distinguish host species, strain and introduced construct in annotations. AI M6: prior×likelihood gives an unnormalized posterior; normalize to obtain probabilities. Do the coin update in the probability primer and explain how evidence changes uncertainty. For genetics exercises choose stable tasks by concept, for example HAMM for sequence differences and PROT for translation, checking prerequisites before adding more.

### Biology/domain assignment retained from the plan

Source unit: B6 · Genetic engineering and industrial strains

Material: *Microbiology* ch. 12 "Modern Applications of Microbial Genetics"; *Biology 2e* ch. 17.1

Produce: Notes; Rosalind 5-8

Understanding check: You understand what "engineered *Yarrowia*" or "recombinant *E. coli*" means in a FermLit paper

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

Source unit: M6 · Probability, the useful part

Material: Murphy, *Probabilistic Machine Learning: An Introduction* ch. 2 (probability) and 4.1-4.3 (statistics) — probml.github.io (free PDF); or Statistical Rethinking 2024 lectures 1-2 (github.com/rmcelreath/stat_rethinking_2024)

Produce: Notes; a Bayesian update by hand

Understanding check: You can explain a posterior with coins

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-W06%20Notebook) or [the complete weekly deck](http://127.0.0.1:5000/learn?week=6). 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 |
|---|---|---|---|
| [Datasheets for Datasets: Gebru et al. — search; resolve first](https://scholar.google.com/scholar?q=Datasheets+for+Datasets%3A+Gebru+et+al.) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-9209c843) | core / Monday | Build-block reading · Datasheets for Datasets: Gebru et al. (2021), Communications of the ACM 64(12):86-92. The questions your guidelines and dataset card must answer | 30 min (estimate) |
| [OpenStax Microbiology ch. 12.1-12.2 "Modern Applications of Microbial Genetics" — search; resolve first](https://duckduckgo.com/?q=OpenStax+Microbiology+ch.+12.1-12.2+%22Modern+Applications+of+Microbial+Genetics%22) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-49a2251c) | core / Tuesday | OpenStax Microbiology ch. 12.1-12.2 "Modern Applications of Microbial Genetics" (60 min) | 60 min |
| [Rosalind problems 5-8 — search; resolve first](https://duckduckgo.com/?q=Rosalind+problems+5-8) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-dd612b06) | core / Tuesday | Rosalind problems 5-8 | 30 min (estimate) |
| [Statistical Rethinking 2024 — source](https://github.com/rmcelreath/stat_rethinking_2024) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-c423e93c) | core / Thursday | Statistical Rethinking 2024, lectures 1-2 (YouTube, from github.com/rmcelreath/stat_rethinking_2024) or Murphy, Probabilistic Machine Learning: An Introduction, ch. 2 — probml.github.io/pml-book/book1.html (75 min). Pick Rethinking if you want stories; Murphy if you want equations | 75 min |
| [Artstein & Poesio (2008), "Inter-coder agreement for computational linguistics" — search; resolve first](https://scholar.google.com/scholar?q=Artstein+%26+Poesio+%282008%29%2C+%22Inter-coder+agreement+for+computational+linguistics%22) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-b0e186e8) | deeper / Saturday · sandbox, optional | Artstein & Poesio (2008), "Inter-coder agreement for computational linguistics", Computational Linguistics 34(4):555-596, sections 1-2. The bible of annotation agreement | 30 min (estimate) |
| [McHugh (2012), "Interrater reliability: the kappa statistic" — search; resolve first](https://scholar.google.com/scholar?q=McHugh+%282012%29%2C+%22Interrater+reliability%3A+the+kappa+statistic%22) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-c3224a87) | deeper / Saturday · sandbox, optional | McHugh (2012), "Interrater reliability: the kappa statistic", Biochemia Medica 22(3):276-282. Short, open, written for biomedical readers | 30 min (estimate) |
| [3Blue1Brown "Bayes theorem, the geometry of changing beliefs" — search; resolve first](https://www.youtube.com/results?search_query=3Blue1Brown+%22Bayes+theorem%2C+the+geometry+of+changing+beliefs%22) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-2867c748) | deeper / Saturday · sandbox, optional | 3Blue1Brown "Bayes theorem, the geometry of changing beliefs" (YouTube, 15 min) | 15 min |
| [STRENDA guidelines (Standards for Reporting Enzymology Data) — search "STRENDA guidelines" — search; resolve first](https://github.com/search?q=STRENDA+guidelines+%28Standards+for+Reporting+Enzymology+Data%29+%E2%80%94+search+%22STRENDA+guidelines%22&type=repositories) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-5bd216b8) | deeper / Saturday · sandbox, optional | STRENDA guidelines (Standards for Reporting Enzymology Data) — search "STRENDA guidelines" (verify URL). A real "minimum information" standard; it shows what a reporting checklist looks like and will inspire your completeness analysis | 30 min (estimate) |
| [HumanSignal/label-studio — source](https://github.com/HumanSignal/label-studio) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-23b27e56) | run / Any block this week — the plan names no day | pip install label-studio, create a text-span project with 5 FermLit fields; annotate 2 papers to feel the difference from JSON-by-hand. Use it only if it speeds you up | 30 min |
| [doccano/doccano — source](https://github.com/doccano/doccano) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-b3019c9e) | run / Any block this week — the plan names no day | Lighter alternative for span annotation; compare in 15 minutes, pick one, never revisit | 15 min |
| [argilla-io/argilla — source](https://github.com/argilla-io/argilla) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-ca0f8878) | run / Any block this week — the plan names no day | Read the "human feedback on LLM outputs" quickstart; you will use this pattern in week 7 to correct agent outputs | 30 min |
| [pymc-devs/pymc-resources — source](https://github.com/pymc-devs/pymc-resources) · [card](http://127.0.0.1:5000/learn?week=6#card-w06-9d23e5b7) | run / Any block this week — the plan names no day | Colab: Statistical Rethinking chapter 2 notebook (grid approximation); do the globe-tossing update by hand, then in code | 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 | Write field-by-field definitions, units, examples, ambiguity rules and adjudication procedure; annotate the first 15 papers while timing the first three. Stop when: Each annotated value has a source sentence and document locator. |
| Tuesday | 90 min | *Microbiology* ch. 12 "Modern Applications of Microbial Genetics"; *Biology 2e* ch. 17.1 Produce: Notes; Rosalind 5-8 |
| Wednesday | 90 min | Annotate the next 20 target papers independently of model outputs; revise guidelines with versioned ambiguity decisions. Stop when: Completed and incomplete records are counted, with no model labels passed off as human gold. Reserve the last 10 minutes for the optional Wednesday note. |
| Thursday | 90 min | Murphy, *Probabilistic Machine Learning: An Introduction* ch. 2 (probability) and 4.1-4.3 (statistics) — probml.github.io (free PDF); or Statistical Rethinking 2024 lectures 1-2 (github.com/rmcelreath/stat_rethinking_2024) Select material/exercise that fits 60 minutes; use the last 30 for the founder paper. |
| Friday | 90 min | Finish the 50-paper target and prepare two annotator invitations for 30 overlapping papers; schedule blinded handoff and return by week 10. Stop when: Gold target is met or shortage logged; external acceptance is evidenced separately. |
| 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 — `annotation-guidelines.md`

**Do these steps in order.**

1. Write a field guide with definition, allowed states, unit policy, a positive example and an ambiguous example for every field.
2. Annotate the first three papers while timing each task; record actual minutes so the 50-paper target can be assessed against capacity.
3. Continue toward the first 15 using source text, not model suggestions.
4. Attach a sentence or table locator to every positive label and mark unresolved interpretation explicitly.

**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:** Write field-by-field definitions, units, examples, ambiguity rules and adjudication procedure; annotate the first 15 papers while timing the first three. Acceptance: Each annotated value has a source sentence and document locator.

**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 — `annotation-progress.csv`

**Do these steps in order.**

1. Annotate the next target group of 20 papers with the same guideline version.
2. Keep an ambiguity log with paper_id, field, competing interpretations and provisional decision.
3. If a rule changes, record its version and recheck affected earlier labels.
4. Save incomplete records as incomplete; do not count a downloaded paper as annotated.
5. Use development papers for rule refinement and retain a genuinely frozen evaluation group.

**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:** Annotate the next 20 target papers independently of model outputs; revise guidelines with versioned ambiguity decisions. Acceptance: Completed and incomplete records are counted, with no model labels passed off as human gold.

**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 — `annotator-brief.md`

**Do these steps in order.**

1. Complete as much of the 50-paper target as the measured time permits and record any shortage.
2. Prepare 30 overlapping papers for a second human, including the instructions and blank annotation form but excluding your labels and model outputs.
3. Specify return date, confidentiality boundaries and how disagreements will later be resolved.
4. Prepare the invitations; independent annotation is only achieved when another person actually returns their work.

**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:** Finish the 50-paper target and prepare two annotator invitations for 30 overlapping papers; schedule blinded handoff and return by week 10. Acceptance: Gold target is met or shortage logged; external acceptance is evidenced separately.

**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 annotation: a table reports “12 ± 2 g L−1, n=3.” Store the central value 12, reported spread 2 with its stated type if known, n=3 and the original text. Do not silently assume the ± is a confidence interval. If the caption does not define it, store “spread type unclear.”

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

The second annotator sees your labels and agrees with 29 of 30. Is that a blinded independent agreement estimate? How would you repair the protocol?

Your answer: ____________________

Your connection to `annotation-guidelines.md`: ____________________

### Answer key

No. Seeing your labels can influence the answers. Use a fresh overlap sample or transparently report the unblinded limitation; provide source documents and guidelines without first-annotator answers. An LLM response does not replace the second human.

### 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 `annotation-guidelines.md` or its preparation instructions. What exact input, action, output and acceptance check make it inspectable?
4. What could make `annotation-progress.csv` look convincing while still being wrong? Use the week-specific risk below and name the evidence needed to detect it.
5. What does `annotator-brief.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 an enabling week. Its deliverables feed the next scheduled gate: 8. Complete the acceptance checklist below; do not promote reputation from a draft.

- [ ] Monday artifact satisfies: Each annotated value has a source sentence and document locator.
- [ ] Wednesday artifact satisfies: Completed and incomplete records are counted, with no model labels passed off as human gold.
- [ ] Friday artifact satisfies: Gold target is met or shortage logged; external acceptance is evidenced separately.
- [ ] 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

Fifty papers in three build blocks is a feasibility risk. Project time from the first three; use Saturday and request a scope/schedule decision if needed. Never fabricate completion or replace the second human with an LLM.

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: 50 gold JSONs.

Operational first step if stalled: open `annotation-guidelines.md`, 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-W06 · human gold standard**.
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

Show two separate human annotation paths from the same papers, followed by comparison and then adjudication; never merge them before comparison.

### Copy-ready prompts

**Concept map / infographic**

> Using only the sources in LABLOOP-W06, explain “human gold standard” to an adult software/systems/AI professional rebuilding science foundations after twenty years. Show two separate human annotation paths from the same papers, followed by comparison and then adjudication; never merge them before comparison. 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 06: 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 06 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 06. 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.