17.1
Literature Discovery Logs and Screening Fields
A discovery log should retain queries, dates, platforms, screening reasons, and final primary sources. Query combinations can include GraphRAG and evaluation, multimodal knowledge graph and entity linking, ingredient retrieval and CMIngre, plus task terms. Broad searches discover branches; exact titles locate originals and datasets. Exclusion reasons such as absent methods, news republication, or uncertain versions explain selection. A narrative review need not claim exhaustive retrieval, but its choices should be understandable.
This report uses Consensus and SciSpace for discovery and checks paper pages, publication records, author datasets, or official documentation. Generated summaries and limitations are not automatically author conclusions. Criticism of baselines must not become limitations attributed to a new method. Reading scope distinguishes articles, workflow sections, and abstract records. A future systematic review could add databases, preregister criteria, and use multiple screeners, but that is a separate study. The worksheet preserves what later researchers need to read and verify rather than treating result counts as quality.
17.2
A Claim and Evidence Register
An important claim can occupy one register row containing identifier, wording, type, source, location, conditions, support strength, and verification status. Types include reported result, cross source synthesis, design recommendation, and demonstration calculation. Results retain experimental scope; syntheses list reasoning; recommendations state validation goals; calculations supply inputs and formulas. Distinct components in one paragraph then do not disappear behind one broad citation. Alternative explanations encourage active counterexample search.
Verification can use two passes. First check source existence, title and date, and copied numbers. Then check actual support and whether scope expanded. Percentages need denominators and units; comparisons need configurations. Missing evidence should not be filled with fluent prose. Incomplete support requires narrower wording or a hypothesis label. Bilingual claims can share a row to compare quantifiers, negations, and time. The register reduces lost conditions and citation drift in long and repeatedly revised reports rather than merely adding paperwork.
17.3
A Graph Data Contract Checklist
A data contract defines object types and identity rules before relation direction, qualifiers, and allowed states. Dish versions need creation, effective and expiry rules, overlap policy, and confirmation responsibility. Ingredient observations distinguish affirmation, negation, and unknown rather than treating missing Boolean values as false. Resource locations should survive filename changes. Model outputs retain method versions, and human edits create new records instead of overwriting history.
Ingestion tests can include duplicate identifiers, same named distinct objects, missing units, reversed times, unsourced relations, and contradictory observations. Invalid structures should be rejected or isolated; a successful database write is not quality acceptance. Export and reconstruction should confirm evidence does not depend on private interface state. Every field needs an owner, validation rule, downstream purpose, and missing value behavior. Contract changes need versions and migration notes. The worksheet turns an ontology into executable constraints and gives data providers and developers a shared quality language.
17.4
Experiment Run Cards and Configuration Records
A run card records hypotheses, inputs, splits, code, model identifiers, prompts, seeds, retrieval budgets, and execution time. Services may not be fully reproducible, so uncontrollable factors such as external model changes and approximate search randomness also matter. Results link to run cards, including failed runs. Before comparison, confirm that only intended factors changed; otherwise configuration drift may explain score differences.
Cards should distinguish executed, partially executed, and planned work. Failed calls should not receive guessed outputs, and unrun ablations remain unreported. Analyses may include overall and grouped metrics, errors, and costs within actual execution scope. This report's run card specifies manual relations, seven records, deterministic queries, and five checks, with no language or visual inference results. Scripts reproduce the numbers. Real studies can add dependency locks and permitted response archives. Reproducibility means providing conditions sufficient to explain and retest main conclusions, not promising identical text in every future environment.
17.5
Figure Data and Visual Verification Worksheets
Each figure needs a purpose, source, units, calculation steps, chart type, and intended observation. Relationship diagrams need labeled directions, quantity plots axes and bases, and workflows a distinction between sequence and dependency. Stable colours should be reinforced by words or line types for monochrome reading. Source figures and original redrawings need separate attribution, and crops must retain context. Assumed data should be labeled directly in titles or captions rather than only in distant prose.
Verification has content and layout layers. Content checks values, units, labels, textual references, causal implications, and exceptions. Layout checks type size, cropping, overlap, resolution, and pagination at actual embedded size. Complex figures can split into overview and detail rather than compress an entire system onto one page. Editable sources should retain text and shapes instead of only low resolution screenshots. Attached SVG and data support later teaching adaptation. Visual quality means helping accurate judgment rather than maximizing decoration or colour.
17.6
Pilot Decisions and Review Records
A pilot decision sheet can record target tasks, baseline, expected gains, critical risks, resources, and stopping conditions. Gains should be observable, such as fewer evidence omissions or shorter verification time, rather than generic intelligence claims. Risks should follow actual scenario failures. Stopping conditions need actions, such as narrowing scope after persistent critical errors or delaying expansion without maintenance ownership. This gives technical and management discussion a common factual basis.
Reviews compare initial assumptions with current evidence and record reasons to retain, adjust, or stop. Failure does not prove permanent uselessness, but changing goals repeatedly should not make every pilot successful. Define primary measures and acceptable changes beforehand and report exploratory findings separately. Adoption needs maintenance ownership and a next review date; simplification can preserve inventories, identifiers, and tests. Research outcomes include knowing which conditions work, not only a final system. Transparent decisions accumulate experience and permit reassessment under new data and models instead of repeating an unexplained trial.