PS1-22: Tumor--VDW Table Structure Dictated by National Agency Standards
Bibliographic record
Abstract
Background: North American Association of Central Cancer Registries (NAACCR) was established in 1987 as a collaborative organization for cancer registries, government agencies, professional associations and private groups.NAACCR develops and promotes uniform data standards, provides education and training, certifies population-based registries, processes and publishes data from central registries and promotes the use of cancer surveillance data for research, public health and patient care.Cancer registries in the US include the national central registries, NCI-SEER and CDC-NPCR, individual State registries and hospital-based (care providerbased) registries.The Cancer Research Network (CRN) has adopted NAACCR data standards to define the Virtual Data Warehouse tumor registry table (VDW-TR).However, since the inception of the VDW-TR, there have been many version of NAACCR in effect.Aims/Methods: VDW-TR needed to have similar and merge-able data for multi-site projects.Data standards set by NAACCR are optimal for construction of this resource as they are designed to collect tumor data centrally from multiple data sources.The standards establish processes for data exchange and record layout in addition to coordinating input from sponsoring organizations, such as AJCC and NCI.NAACCR is also responsible for incorporating new items of interest as the data used to characterize cancers evolve.We describe how these changes were incorporated into the VDW-TR.Results: AJCC Collaborative Stage I (CS-1), applicable to cases diagnosed beginning with January 2004, brought many changes to data and data formats required for staging.These changes were not incorporated by the VDW tumor file in 2004 due to the lack of ownership and oversight.Discrepancies eventually developed between VDW data dictionary and NAACCR causing data value decay.ICDO-2 histology lists were expanded and recoded in ICDO-3, providing additional challenges, along with other rules-based changes in tumor classification.CS-1 also mandated addition of anatomic site specific factors.Many additional changes occurred in 2010 with CS-2.The specifications incorporated in our current VDW-TR address all of these data changes.Conclusion: The VDW has to adopt NAACCR changes as they are adapted to remain current with all standards.We are now sensitized to monitor and adjust for significant future changes in NAACCR.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.028 |
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".