Bibliographic record
Abstract
Education in dentistry as in medicine is guided principally by the ontology and theory of science, which provides definitions of health and disease, legitimizes research methods, and influences the role of the clinician. The challenge of managing chronic oral disease and disability prompts interest in social theory as much as science. Therefore, dental geriatrics requires a solid foundation in the humanities from the belief that the determinants of health and the cause of chronic diseases lie within an intermingling of biology, economics, sociocultural structure, and human behavior. The dental curriculum in many places is reorganizing from the horizontal foundation of basic sciences to an integration of foundational and clinical knowledge focused on clinical competencies and integrated care. The impact of this integration on dental geriatrics necessitates a more humanistic and naturalistic perspective in dental education to balance and challenge the current evidence for best clinical practice, which at present is based almost exclusively on science. Consequently, dental students should be exposed to a consilience of the science and the humanities if dentists are to address effectively the needs of an aging population.
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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".