Bibliographic record
Abstract
When Mr. B attends his brother’s dentist (who has been highly recommended for his compassion and honesty) for the first time, he has a toothache in the upper left bicuspid area. A radiograph reveals large distal caries on both tooth 24 and tooth 25. Tooth 25 also exhibits rarefying osteitis apically, whereas tooth 24 has an intact lamina dura. The results of vitality tests are normal for tooth 24, but tooth 25 has no response to cold or electrical stimulus. Root canal treatment is recommended for tooth 25. The options and costs of the treatment, which includes a post and core and subsequent crown, are explained, and Mr. B gives consent to proceed. The patient is also informed of the possibility that root canal treatment may be needed for tooth 24 because of deep progression of the caries, and this discussion is noted in the records. An anesthetic is delivered, and the dentist instructs his
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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 | 0.014 | 0.112 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.015 | 0.023 |
| Insufficient payload (model declined to judge) | 0.052 | 0.013 |
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".