execution-plan/weeks/week-10-annotation-agreement-and-analysis/learning-notebook.md · UPDATED 2026-10-01
LABLOOP W10 — annotation agreement and analysis: 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 · Commitment · Evidence · Review · Notebook index and export guide · NotebookLM upload text
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1. The week in plain language: what, why and where it leads
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1. The week in plain language: what, why and where it leads
Two people may read the same paper differently. This week measures that disagreement before resolving it, then creates the first descriptive figures from FermLit. Agreement tells you how consistently the annotation rules can be applied. Descriptive analysis tells you what is in your selected corpus; it does not prove that one organism or process causes better production.
Your systems, software and AI connection. You are validating the measurement system before interpreting its outputs. This is like assessing sensor repeatability before trusting a process dashboard. Your analysis and figure generation should be scripted so the same versioned rows produce the same counts, captions and plots.
Dependency map from the existing programme.
- ← From: week 6 gold set + second annotator; week 9 2,000 records.
- → Feeds: week 11 (formal completeness result), week 13 (Paper 1 skeleton figures), week 14 (Methods), week 16 (conformal prediction extends the GP's uncertainty idea), week 34 (judge-human agreement in labdocs).
- ⟳ Returns in: Paper 1 "Annotation agreement" paragraph and figures 1-4.
Gate and proof required by the current weekly specification.
This is an enabling week. Its deliverables feed the next scheduled gate: 13. 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.
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2. Before starting: locate inputs and repair only the needed foundations
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2. Before starting: locate inputs and repair only the needed foundations
- Week 06: inspect its actual evidence and review; source/code artifacts must exist before the dependent task begins.
- 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.
- 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.
- 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.
- 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.
- 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.
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3. Foundation refreshers you can use without another notebook
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3. Foundation refreshers you can use without another notebook
Units, ratios and balance checks
A unit tells you what a number measures. Concentration=amount/volume; rate=change/time. Write the units through each calculation as if they were types in a programming language. Adding grams to liters is a type error; dividing grams by liters produces a concentration. Convert compatible quantities before comparison: 1,000 mg=1 g, so 2,500 mg/L=2.5 g/L. Never discard the original value and source string.
Percent needs a definition of numerator and denominator. “2%” might mean grams per 100 mL, grams per 100 g or mL per 100 mL. Those cannot always be converted without density or other context. Likewise endpoint concentration divided by total time is not always the scientific productivity definition used by an author.
A mass balance says accumulated amount = inputs − outputs + production − consumption. In a variable-volume tank, track amount C×V as well as concentration C: adding water can lower concentration without removing material. For fed-batch with no outflow, dV/dt=F and dilution terms often contain F/V. If F is L/hour and V is L, F/V has unit 1/hour. Units are a fast first defense against equations or extraction conversions that look plausible but cannot be right.
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 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.
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.
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4. This week’s specific study bridge
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4. This week’s specific study bridge
Domain B10: yield is output per consumed input, such as Y_XS=biomass formed/substrate consumed. Maintenance represents consumption not used to form new biomass. AI M10: a Gaussian process places a probability model over functions using a covariance/kernel that encodes similarity. Nearby observations can influence predictions together; uncertainty depends on the kernel, noise assumptions and data. Fit a small development example and inspect a distant prediction rather than treating the band as automatically calibrated.
Biology/domain assignment retained from the plan
Source unit: B10 · Bioreactors II: kinetics and yields
Material: NPTEL lectures 4-6 (Monod, yields, maintenance)
Produce: Yield coefficients computed on IndPenSim
Understanding check: You can explain Yx/s and Yp/x
AI/scientific-method assignment retained from the plan
Source unit: M10 · Gaussian processes
Material: Rasmussen & Williams, GPML ch. 1-2 — gaussianprocess.org/gpml (free); scikit-learn GP examples
Produce: GP soft sensor with uncertainty bands
Understanding check: You can explain a kernel as "similarity"
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.
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5. Resource stashes: open, study, apply and retain
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5. Resource stashes: open, study, apply and retain
Open this week’s resource stash or the complete weekly deck. 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 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 |
|---|---|---|---|
| McHugh — search; resolve first · card | core / Monday | Build-block reading · McHugh (2012) kappa paper (carry over from week 6), results interpretation table | 30 min (estimate) |
| NPTEL Bioreactors — search; resolve first · card | core / Tuesday | NPTEL Bioreactors lectures 4-6 (Monod, yields, maintenance) (75 min) | 75 min |
| Rasmussen & Williams, Gaussian Processes for Machine Learning, ch. 1-2 — gaussianprocess.org/gpm… — source · card | core / Thursday | Rasmussen & Williams, Gaussian Processes for Machine Learning, ch. 1-2 — gaussianprocess.org/gpml (free) (45 min) after Görtler, Kehlbeck & Deussen (2019), "A Visual Exploration of Gaussian Processes", Distill — distill.pub/2019/visual-exploration-gaussian-processes (30 min, interactive; start here) | 45 min |
| ritvikmath "Gaussian Processes" — search; resolve first · card | deeper / Saturday · sandbox, optional | ritvikmath "Gaussian Processes" (YouTube, whiteboard intuition) | 15 min (estimate) |
| StatQuest "Confidence Intervals, Clearly Explained" and "The Standard Error" — search; resolve first · card | deeper / Saturday · sandbox, optional | StatQuest "Confidence Intervals, Clearly Explained" and "The Standard Error" | 15 min (estimate) |
| Krippendorff's alpha — search; resolve first · card | deeper / Saturday · sandbox, optional | Krippendorff's alpha (Wikipedia page is good) for when you have more than two annotators or missing ratings | 30 min (estimate) |
| Modern Statistics for Modern Biology (Holmes & Huber) ch. 3 "High quality graphics in R" — search; resolve first · card | deeper / Saturday · sandbox, optional | Modern Statistics for Modern Biology (Holmes & Huber) ch. 3 "High quality graphics in R" — read for the design principles, ignore the R | 30 min (estimate) |
| scikit-learn/scikit-learn — source · card | run / Any block this week — the plan names no day | sklearn.metrics.cohen_kappa_score per field; gallery example "Gaussian process regression: basic introductory example" | 30 min |
| cornellius-gp/gpytorch — source · card | run / Any block this week — the plan names no day | "Simple GP Regression" tutorial notebook in Colab; add predictive variance bands to one soft-sensor feature | 30 min |
| pln-fing-udelar/fast-krippendorff — source · card | run / Any block this week — the plan names no day | Compute alpha on the same annotations; compare with kappa and write one sentence on why they differ | 30 min |
| plotly/plotly.py / mwaskom/seaborn — search; resolve first · card | run / Any block this week — the plan names no day | Build figure 1 (completeness by field) as a static, publication-ready image | 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.
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6. Seven-day runbook: what to do, why and when to stop
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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 | Receive the second human's independent 30-paper annotations, calculate categorical agreement/kappa and numeric tolerance agreement, then adjudicate. Stop when: Pre-adjudication labels are retained and agreement is reported by field and support. |
| Tuesday | 90 min | NPTEL lectures 4-6 (Monod, yields, maintenance) Produce: Yield coefficients computed on IndPenSim |
| Wednesday | 90 min | Analyze titer/product/organism, scale and reporting patterns with denominators and comparable units. Stop when: Exploratory comparisons are labeled; no causal or cross-product efficacy claims. Reserve the last 10 minutes for the optional Wednesday note. |
| Thursday | 90 min | Rasmussen & Williams, GPML ch. 1-2 — gaussianprocess.org/gpml (free); scikit-learn GP examples Select material/exercise that fits 60 minutes; use the last 30 for the founder paper. |
| Friday | 90 min | Generate Paper 1 figures 1–4 with frozen data/version and export static versions plus captions. Stop when: One command regenerates each plot and caption N agrees with the table. |
| 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 — agreement-report.md
Do these steps in order.
- Receive the second human annotations and retain both original files unchanged.
- Join on paper/experiment/field keys and verify the overlap count.
- For categorical fields calculate raw agreement and, where appropriate, Cohen’s kappa with category counts.
- For numbers use valid unit conversion and predefined tolerance agreement plus difference plots.
- Calculate these before adjudication, then record resolutions in a third file.
- Missing independent labels leave that part pending.
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: Receive the second human's independent 30-paper annotations, calculate categorical agreement/kappa and numeric tolerance agreement, then adjudicate. Acceptance: Pre-adjudication labels are retained and agreement is reported by field and support.
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 — descriptive-analysis.md
Do these steps in order.
- Choose comparable product/organism groups and state the unit of analysis.
- Summarize distributions, medians or other justified effect sizes with group counts.
- Do not pool incompatible products into a league table.
- Inspect missingness and assay/scale context.
- Label exploratory comparisons as exploratory and preserve the query/filter code behind each summary.
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: Analyze titer/product/organism, scale and reporting patterns with denominators and comparable units. Acceptance: Exploratory comparisons are labeled; no causal or cross-product efficacy claims.
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 — figure-inventory.md
Do these steps in order.
- Create a figure inventory for the first four Paper 1 figures: question answered, input table/hash, command, axes/units, N, caption and caveat.
- Regenerate static figures from the frozen analysis table.
- Check that caption denominators agree with the source counts.
- Use an explicit unavailable panel or pending entry if evidence is missing rather than manufacturing a completed figure.
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: Generate Paper 1 figures 1–4 with frozen data/version and export static versions plus captions. Acceptance: One command regenerates each plot and caption N agrees with the table.
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
- Spend 10 minutes recalling what you know and listing the specific confusing words in the domain assignment above.
- 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.
- 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.
- Spend 10 minutes explaining what the concept changes in this week’s work. Record the explanation or write five sentences without looking.
- 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.
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7. Worked example, practice and separate answer key
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7. Worked example, practice and separate answer key
Worked teaching example
Synthetic agreement example: observed agreement is 0.90 and agreement expected from the annotators’ category frequencies is 0.80. Kappa=(0.90−0.80)/(1−0.80)=0.50. This illustrates why raw agreement and category prevalence matter. It is not a universal pass threshold, and kappa is not the right direct calculation for raw continuous titer values.
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
Annotator A records 1 g/L and B records 1,000 mg/L. Is this disagreement? What must you retain after normalization?
Your answer: ________
Your connection to agreement-report.md: ________
Answer key
The values are equivalent after a valid unit conversion. Retain both original strings, the conversion rule and normalized values. Other context, such as which experiment was measured, must also agree; numeric equivalence alone is insufficient.
Five recall questions and grading guide
- Explain this week’s purpose to a 15-year-old in three sentences. What real scientific or professional decision does it support?
- Solve the exercise above and explain each assumption or unit, rather than copying the answer.
- Open
agreement-report.mdor its preparation instructions. What exact input, action, output and acceptance check make it inspectable? - What could make
descriptive-analysis.mdlook convincing while still being wrong? Use the week-specific risk below and name the evidence needed to detect it. - What does
figure-inventory.mdpass 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.
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8. Research evidence and professional profile
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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.
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9. Completion checklist, misconceptions and recovery
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9. Completion checklist, misconceptions and recovery
This is an enabling week. Its deliverables feed the next scheduled gate: 13. Complete the acceptance checklist below; do not promote reputation from a draft.
- Monday artifact satisfies: Pre-adjudication labels are retained and agreement is reported by field and support.
- Wednesday artifact satisfies: Exploratory comparisons are labeled; no causal or cross-product efficacy claims.
- Friday artifact satisfies: One command regenerates each plot and caption N agrees with the table.
- 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
Kappa is not an agreement statistic for continuous raw measurements without justified categorization. If the second annotator is delayed, agreement stays pending and downstream release limitations must be explicit.
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: kappa.
Operational first step if stalled: open agreement-report.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: 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.
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10. NotebookLM import and visual study kit
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10. NotebookLM import and visual study kit
- Create a notebook named LABLOOP-W10 · annotation agreement and analysis.
- Upload this week’s
notebooklm.txtorlearning-notebook.md, or paste the complete text as a source. Upload one copy, not both. Google’s source-import guidance documents text/Markdown and pasted-text sources. - 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.
- 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.
- 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
Draw two annotation columns feeding an agreement table before a separate adjudicated gold table; add a figure provenance chain.
Copy-ready prompts
Concept map / infographic
Using only the sources in LABLOOP-W10, explain “annotation agreement and analysis” to an adult software/systems/AI professional rebuilding science foundations after twenty years. Draw two annotation columns feeding an agreement table before a separate adjudicated gold table; add a figure provenance chain. 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 10: 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 10 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 10. 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.
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11. Source and ownership notes
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11. Source and ownership notes
This notebook adds explanation and runbooks to the existing plan. The weekly specification, programme decisions and gates retain authority over sequence, scope and acceptance. The v6 master supplies the dependency map and inherited resource cards; the source catalog 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.