Week 02 — indpensim data and baseline

This week delivers the three concrete artifacts below and the supporting learning/branding/opportunity pack. The scientific or commercial outcome follows the preserved source brief, while the acceptance checks make its evidence testable. The career objective is to turn this work into something a scientist, hiring manager or buyer can inspect.

• Scientific/build priority: Record the authoritative IndPenSim source, access terms, checksums and metadata; implement tidy import and count actual available batches.
• Public/profile priority: Prepare the first Medium thesis article from v4 and one annotated data figure; label the data simulated.
• Career/relationship/commercial priority: Select an initial five-founder feedback list and draft a non-sales question supported by this week's paper digest.

Read v6 · Week 2 · One hundred real batches before Monday. It carries this week's v5 brief unchanged and adds the Welcome analogy, Learn it (▶ core and ＋ deeper sources), Run it (repos with a 20-40 minute exercise), the NotebookLM kit and the mentor check below. Standing v6 rules: resource rules, NotebookLM protocol, chapter anatomy. v6 adds depth only; it does not change a goal, gate, output or the 600-minute cap, so this specification still governs execution.

Verified links, exact scopes and durations for this week's reading and watching: materials.md.

Act I · Threads: B, M, BL · Next gate: 4

Where this week sits. - ← From: week 1 (you know what X, S, P and DO mean because you invented them). - → Feeds: week 3 (PCA scores become Hotelling T² alarms), week 4 (hours-to-detection needs aligned batches), week 8 (soft sensor uses the tidy parquet), weeks 12 and 17 (Paper 2 is built on this dataset). - ⟳ Returns in: Paper 2 "Data" section; you will cite Goldrick et al. 2015 and 2019.

Goals. - 🎯 This week: IndPenSim as a tidy parquet that loads in under a minute; an overlay plot; faulty batches visible in PCA. - 🏁 Next milestone: Gate 4. - 🌟 Final: the dataset under Paper 2; your first Medium thesis piece (M1) positions you before any paper exists.

Mentor check. "I can explain what a faulty batch looks like in a PCA scores plot and why respiration makes oxygen fall when biomass rises."

• Week 01: inspect its actual evidence and review; source/code artifacts must exist before the dependent task begins.
• Read commitment, evidence, review and the current root TODAY/PROGRESS/QUESTIONS files.
• Read this week's chapter, v6 · Week 2 · One hundred real batches, then the standing sections: Part 0 · how to use the document, Part 3 · the scientific thesis, Part 4 · curriculum, Part 8 · the prompt pack and Part 9 · branding and endorsement. The same sections exist in the v5 master, which remains the governing sequence; v6 reproduces them and adds depth. Retained commercial/instrument details come from v4.
• Inspect the actual canonical repository state, available data, existing figures and required human/external inputs. Never assume a previous week succeeded from its folder name.
• Verify current resource links, versions, dataset rights and any live company/venue information before relying on them. Use source catalog; explicitly record inaccessible resources.

The model must turn these into exact physical actions using the observed files and available inputs. Each 90-minute block includes start/stop rituals. All calls, posts, debugging, reading and exercises consume this same capacity.

Each day is one mission: the Hook gets you in, Done when tells you to stop. Study stops at the understanding check. If a piece feels pointless, ask whether Done when needs it: no → skip and log; yes → let AI do the boring part and review it; still stuck → smallest version in 25 minutes.

Biology/domain unit

Source unit: B2 · The cell and energy

Material: Crash Course Biology #7 "ATP & Respiration" (trimmed 2026-09-29; OpenStax ch. 4, 5 and 7 are Deeper)

Produce: three lines linking respiration to a real DO curve

Understanding check: You can explain why a microbe needs oxygen and sugar in a tank

During preparation, write one worked example connected to the week's actual task, one exercise with a separate answer key and five questions. Peter supplies answers; score explanation quality and flag misconceptions in QUESTIONS. Numeric/scientific conclusions require actual data or explicitly synthetic teaching values.

AI/scientific-method unit

Source unit: M2 · Calculus and the neural network idea

Material: 3Blue1Brown "Essence of Calculus" ch. 1-2 + StatQuest PCA step-by-step (trimmed 2026-09-29; neural networks move to week 8)

Produce: Notes

Understanding check: You can say what dX/dt means in your code and what a principal component is

Use the prompt pack: P1 explanation ladder, P2 concept-to-project bridge and P3 quiz. Coding practice belongs within the allocated study/build block. Where the source asks for a favorable scientific result, substitute an honest measured comparison as explained below.

Founder/scientist paper

Select one verified founder/scientific-lead paper relevant to this week's domain. Use P11; save the question, method, numerical result with context, data workflow, three author questions and one connection sentence in founder-paper.md. Keep abstract-only access limitations explicit. On source weeks with no study, prioritize the commercial/submission task and log any skipped digest.

These filenames are outputs to prepare during this week's execution; this scaffold does not claim they already exist. Drafts and measured results have different states. Technical code/data stay in the canonical project repository and are referenced from these coordinating files.

During preparation, future measured tables get column definitions, input requirements and run instructions with PENDING status. During execution, replace pending values only with measured outputs. Do not create realistic-looking fake evidence.

Branding: Prepare the first Medium thesis article from v4 and one annotated data figure; label the data simulated.

Opportunity action: Select an initial five-founder feedback list and draft a non-sales question supported by this week's paper digest.

Use career asset contracts. Publish at most the agreed cadence; one figure and one supported number or admitted failure can support multiple drafts. In long-form weeks, prepare a 1,500–2,500-word article from existing evidence within the build/buffer allocation. In release/demo weeks, prepare a 60-second script: problem, input, command/action, result, limitation and proof link.

Verify individuals, jobs and affiliations at execution time. The GridX list and v4 company map are research seeds, not current facts. Do not reveal named company weaknesses or employer/client confidential information. Keep drafted/sent/replied/booked/held statuses separate. The planning request alone does not authorize external messages or publication; honor explicit authorization in the execution session.

Do not call these real plant batches or require a visually favorable result. The historical download site may fail; use an author-linked source and preserve provenance.

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.

This is an enabling week. Its deliverables feed the next scheduled gate: 4. Complete the acceptance checklist below; do not promote reputation from a draft.

• Monday artifact satisfies: Batch/time/variable/value data and a reproducible manifest exist; benchmark simulated origin is explicit.
• Wednesday artifact satisfies: Five relevant variables and any use of future information are documented.
• Friday artifact satisfies: A reproducible scores plot exists even if faulty batches do not separate.
• 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.

Source-preserving minimum: the tidy parquet of IndPenSim.

Operational first step if stalled: open data-audit.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.

In review, state exactly what exists, what was verified, what Peter can now explain, which external events remain pending, where the canonical code/data live, and the next file/function or draft paragraph to touch. Link each fact to evidence. Carry scientific assumptions, split definitions and rights constraints forward explicitly.

Prepare Week 02 of this LABLOOP execution plan.
Read execution-plan/specs.md, execution-plan/DECISIONS.md,
execution-plan/GATES.md and
execution-plan/weeks/week-02-indpensim-data-and-baseline/specs.md, commitment.md, evidence.md and review.md.
Read prior prerequisite reviews and inspect actual repository/data state.
Use v5 as the governing sequence, the v6 Week 02 chapter
(LABLOOP-Master-Plan-v6.md) as the deeper walkthrough, and v4 only for
retained details.
Produce the full local preparation pack and the exact week-specific files named
in the artifact table. Give me a bounded lesson with exercises/answer key,
daily physical actions, technical runbook or draft, branding drafts and
career/commercial actions. Keep the total to 600 minutes.
Separate prepared artifacts from measured results and my learning completion.
Verify sources and do not invent metrics, citations, papers, people or outcomes.
Do not execute external communications, publication or spending unless the
current session already authorizes the specific action.
Finish by updating evidence/review and TODAY with the next physical action.

v6 reproduces this brief unchanged inside v6 · Week 2 · One hundred real batches. The following is source planning text, not a claim of completion. Apply the explicit evidence corrections in this specification and DECISIONS.md.

Week 2 · One hundred real batches

• Goal: IndPenSim loaded, understood, and one golden-batch picture.
• Tue (B2): Biology 2e ch. 4, 5.1-5.2, 7.
• Thu (M2): 3Blue1Brown calculus ch. 1-4 + neural networks ch. 1-4. Founder paper 2.
• Build: [ ] Mon: data/download.py for IndPenSim with checksums; load into a tidy long table (batch, time, variable, value). Done when 100 batches load in under a minute from parquet. [ ] Wed: batch unfolding and time alignment; plot every variable for 10 batches overlaid. Done when you can name the 5 variables that matter. [ ] Fri: PCA on the "normal" batches, scores plot, first look at the faulty ones. Done when the faulty batches are visibly outside.
• Sun: L-Sun with the overlay plot. M1 (Medium, thesis piece): "Biotech startups don't have an AI problem" (reuse v4 section 1, archetypes with counts, no names).
• Only one thing: the tidy parquet of IndPenSim.