Special Category - Pan-genomic/Pan-proteomic Approaches to Cancer
Bibliographic record
Abstract
High average observed agreement, sensitivity, and specificity in ER, PR, and HER2 testing was observed (all > 90%). Kappa values were within the target range (> 0.8, or "near perfect" agreement) for all participating laboratories except the following: 1 laboratory for ER, 6 laboratories for PR, and 1 laboratory for HER2. Kendall's coefficient of concordance between the 18 laboratories was 0.942 for ER, 0.930 for PR, and 0.958 for HER2. False positive and false negative results could be identified as either interpretive or technical errors. Conclusions: The first Canadian IHC EQA testing for ER, PR, and HER2 showed very high concordance between laboratories. The anonymous participation and unrestricted full access provides a means for rapid insight into technical or interpretive deficiencies, allowing appropriate corrective action to be taken.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".