American Joint Committee on Cancer Canadian Association of Provincial Cancer Agencies
Bibliographic record
Abstract
Chair, Volume II Subcommittee of the Uniform Data Standards Committee Comments and suggestions on this and other NAACCR standards documents are welcome. Please send your comments to the Editor or any member of the NAACCR Board of Directors. The other volumes in the series, Standards for Cancer Registries, are: Volume I, Data Exchange Standards and Record Description Intended for programmers and selected users of central cancer registry data, this Volume provides the record layouts and specifications for a number of standard NAACCR record formats, including: the standard record layouts for data exchange among central cancer registries; an update/correction record layout; and an analysis record layout that provides standard recodes for grouping selected variables such as race and primary site, as well as algorithms for converting data from one version of the International Classification of Diseases for Oncology to another. Volume III, Standards for Completeness, Quality, Analysis, and Management of Data Intended for central registries, this provides detailed standards for many aspects of the operation of a population-based cancer registry. Volume IV, Standard Data Edits
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.104 | 0.039 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".