Journal of the Canadian Dental Association
Bibliographic record
Abstract
Chronic periodontal disease is an infectious diseasecharacterized by inflammation and subsequentdestruction of the supporting structures of the teeth. The prevalence and severity of attachment loss and bone loss increases with age.1 Management of chronic perio-dontitis generally consists of a combination of surgical and nonsurgical therapies. Nonsurgical therapy involves scaling and root planing to remove subgingival plaque and calcu-lus. There is some evidence that conjunctive use of antibi-otics in the treatment of certain types of periodontal disease may be of benefit to some patients,2 but it is considered to provide no additional advantage over scaling and root plan-ing alone in the treatment of adult chronic periodontitis.3 Numerous surgical techniques are available to treat the destruction caused by this disease. However, the goal of all techniques is to eliminate the local etiology (i.e., plaque and plaque retentive factors) and produce an environment conducive to health. The success of periodontal therapy is usually measured in terms of maintenance or improvement in clinical attach-ment levels. Comparisons of the efficacy of surgical and nonsurgical therapies are equivocal. Some studies have shown that surgery produces better attachment levels after 6 months;4,5 others have found nonsurgical therapy to be more efficacious.6 (In the latter study, teeth were often root planed for up to 45 minutes each, and patients were recalled every 2 weeks). Long-term (4-6 years) results range from no difference4,7 to improved attachment levels after root plan-ing.5 A meta-analysis8 found that, in the short term, the initial amount of attachment loss was the important factor
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.648 | 0.360 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".