LABLOOP W05 — fermlit corpus and schema: full learning notebook

FermLit begins by turning research papers into a well-defined collection and schema. A corpus is a selected set of documents; a schema is the contract describing one record. One paper may contain many strains, conditions and experiments, so one row per paper can mix incompatible values. You are designing an instrument that extracts experimental facts with evidence, not a collection of fluent summaries.

Your systems, software and AI connection. Database modeling, search queries and data lineage are central systems skills here. Biology gives each field its meaning: a strain is a specific microbial lineage, titer is product concentration, and yield compares output with consumed input. The schema and screening decisions determine what Paper 1 can honestly conclude.

Dependency map from the existing programme.

• ← From: week 4 reproducibility habits (manifest, checksums); your v3/Vara experience with LLM pipelines.
• → Feeds: week 6 (the schema becomes annotation guidelines), week 7 (the agent fills the schema), week 9 (corpus scales to 2,000), week 14 (RELATED.md becomes Paper 1's related work).
• ⟳ Returns in: Paper 1 Methods: "Corpus construction" and "Schema".

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.

• Week 04: 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.

Biological quantities behind the software

A cell is a living organized system with a boundary, molecular machinery and reactions. DNA stores sequence information; genes can be transcribed into RNA; protein-coding RNA can be translated into amino-acid chains called proteins. Many proteins are enzymes, catalysts that speed particular reactions. A substrate is a molecule an enzyme acts on, or, in a process model, an available nutrient; context determines the precise meaning. A strain is a particular lineage within an organism species, so species and strain are not interchangeable identifiers.

Cells obtain usable energy through metabolic reactions. ATP is a common molecular energy carrier, not a synonym for food. Oxygen can support respiratory metabolism, but organisms and process conditions differ; oxygen need should be an explicit assumption. In biotechnology, “fermentation” often refers broadly to microbial cultivation, including aerated processes, while biochemical fermentation has a narrower metabolic meaning.

Titer measures product concentration, often g/L. Yield compares product with an input, such as g product/g substrate consumed. Productivity includes time, such as g/L/hour. A higher concentration can coexist with slower production or worse yield. Record the exact quantity your code predicts, how it was measured and its units. This makes a table column a biological measurement rather than just a convenient number.

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.

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.

Biology B5: gene expression links DNA to RNA to protein; overexpression changes the amount produced and does not guarantee an improved process. AI M5: regularization discourages overly complex fitted behavior, while trees split features into regions and boosting adds weak models to reduce remaining error. Tabular boosting is a candidate baseline, not a guaranteed winner. Practice with a tiny development-only soft-sensor comparison. For Rosalind use stable task IDs (DNA, RNA, REVC, GC) rather than the changing website display order.

Biology/domain assignment retained from the plan

Source unit: B5 · DNA to protein

Material: Biology 2e ch. 14 (DNA), 15 (genes and proteins); Crash Course "DNA, Hot Pockets & the Longest Word Ever"

Produce: Notes; Rosalind problems 1-4 (rosalind.info)

Understanding check: You can read "the strain overexpresses gene X" and know what it means

AI/scientific-method assignment retained from the plan

Source unit: M5 · Regularization and trees

Material: ISLP ch. 6.1-6.2 and ch. 8 (trees, boosting)

Produce: LightGBM soft sensor with tuned regularization

Understanding check: You can explain why boosting wins on tabular data

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.

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.

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.

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.

Monday challenge — related-work.md

Do these steps in order.

1. Create a related-work table with citation, research question, dataset/task, available code/data, strengths and the exact gap FermLit could address.
2. Search at least ten candidate works and resolve each reference.
3. Read methods or data documentation before calling a resource comparable.
4. Write one contribution sentence supported by the comparison: a new resource, extension or replication are all possible outcomes.
5. Preserve search strings and dates.

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: Verify at least ten related works and decide whether FermLit is a new resource or an extension; record search strings and date. Acceptance: Every citation resolves and the novelty statement follows the evidence.

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 — corpus-protocol.md

Do these steps in order.

1. Write inclusion/exclusion rules before bulk download: organism/process scope, experimental evidence, usable full text and required access rights.
2. Use a parenthesized Europe PMC query and pilot a small page of results.
3. Screen titles/abstracts, then full text; keep retrieval, eligibility, accessibility and inclusion counts separate.
4. Save stable paper identifiers, version relationships and reasons for exclusion.
5. Expand toward the planned 500 only after the pilot workflow is understandable.

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: Pilot the parenthesized Europe PMC query, screen eligibility and acquire up to the 500-paper target with a license-aware manifest. Acceptance: Retrieved, eligible, accessible and included counts are separately reported.

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 — schema-review.md

Do these steps in order.

1. Hand-map three papers, including one with several conditions.
2. Give paper_id and experiment_id separate fields.
3. For each measurement preserve original text, normalized value, unit, source sentence/table cell and locator.
4. Use explicit states for present, not reported, inaccessible and extraction failed.
5. Define how host, strain, product, titer, yield and productivity differ.
6. Revise the schema when a real example does not fit, and version the change rather than forcing unrelated measurements into one row.

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: Define experiment-level records and provenance fields; hand-map three papers with multiple conditions; save raw and normalized units. Acceptance: Schema distinguishes paper, experiment, missing, not reported, and extraction failed.

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.

Worked teaching example

Synthetic paper example: strain A reaches 5 g/L in condition 1 and strain B reaches 8 g/L in condition 2. A paper-level row combining strain A with 8 g/L would describe an experiment that never happened. Two experiment records tied to their own table cells preserve the association.

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

A paper gives 5 g/L after 10 hours. Is this automatically a yield of 0.5 g/g? What additional quantity would a yield require?

Your answer: ________

Your connection to related-work.md: ________

Answer key

No. Dividing concentration by time gives an average volumetric productivity of 0.5 g/L/hour under the stated interval, not a mass yield. A mass yield needs product mass and consumed substrate mass, with compatible boundaries and units.

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 related-work.md or its preparation instructions. What exact input, action, output and acceptance check make it inspectable?
4. What could make corpus-protocol.md look convincing while still being wrong? Use the week-specific risk below and name the evidence needed to detect it.
5. What does schema-review.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.

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.

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.

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: Every citation resolves and the novelty statement follows the evidence.
• Wednesday artifact satisfies: Retrieved, eligible, accessible and included counts are separately reported.
• Friday artifact satisfies: Schema distinguishes paper, experiment, missing, not reported, and extraction failed.
• 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

Do not equate search hits with fermentation experiments. Scientific Data claims and company gaps are hypotheses. Freeze paper-level development/test partitions before annotation or prompt tuning.

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: RELATED.md. If someone did it already, you must know now.

Operational first step if stalled: open related-work.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.

1. Create a notebook named LABLOOP-W05 · fermlit corpus and schema.
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 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

Draw a paper containing two experiments, each with its own organism, condition, value/unit and arrow back to a table cell.

Copy-ready prompts

Concept map / infographic

Using only the sources in LABLOOP-W05, explain “fermlit corpus and schema” to an adult software/systems/AI professional rebuilding science foundations after twenty years. Draw a paper containing two experiments, each with its own organism, condition, value/unit and arrow back to a table cell. 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 05: 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 05 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 05. 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.

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.