Calidad de la canal del cordero lechal. Evaluación de dos métodos de estimación subjetiva del contenido de músculo, grasa y hueso
Bibliographic record
Abstract
The authors sent a questionnaire to a random sample of general dentists in Ontario, Canada, to assess the types of non-clinical information (NCI) dentists usually obtain during initial examinations of older patients. From a list of 11 NCI questions, dentists indicated which questions they usually asked during new patient examinations. The adjusted response rate was 34% (n = 672). Respondents most often asked about pain and satisfaction with the appearance of teeth and/or dentures. About half the respondents asked about oral dryness and whether problems with chewing had limited food choices. Respondents were least likely to ask about problems with speaking and avoidance of eating with others because of chewing problems. Traits of those who asked the least common NCI questions typically including continuing education courses in geriatric dentistry, self-perceived competence in treating elderly adults living in institutional settings, exposure to geriatric outreach settings during dental school and greater dentist involvement in patient history taking.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".