Bibliographic record
Abstract
Third molar extraction is one of the most common oral surgeries performed on Canadian patients, particularly young adults. Vigorous debate persists about the risks of retention of asymptomatic impacted third molars, compared to extraction. The controversy centres on whether medical necessity justifies the cost of third molar extraction for the patient in terms of substantial pain and potential loss of income during recovery and for the federal or provincial health care systems, which may be billed for a portion of the surgical fees. Several research studies initiated by the American Association of Oral and Maxillofacial Surgeons (AAOMS) report new associations between oral disease and asymptomatic impacted third molars. These findings merit careful attention because they are being used by the AAOMS to advocate for prophylactic third molar extraction--an approach that contradicts the conclusions of a Canadian health technology report, American Public Health Association policy, and health technology reports from Sweden, Belgium and the UK. The decision to extract third molars seems most effective when made on a case-by-case basis that is tailored to each patient's health status and access to professional oral health care.
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 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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.028 | 0.008 |
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".