Bibliographic record
Abstract
American dentistry has recognized for a quarter century that the growth in the proportion of elderly in the population is impacting on the profession. Multiple articles in the professional literature have speculated on the ways in which this change will be manifested. Data and projections from earlier articles are revisited and five trends are offered to guide professionals as they position their practices for the coming years. The increase in number and proportion of elderly in dental practices stems from successes in preventing and controlling infectious diseases during the last century. The trend has not peaked but will continue for at least two more decades. Retention of teeth into advanced age has resulted from emerging and improved preventive and restorative dental advances directed at children and adults beginning mid-century, and dental utilization studies confirm the elderly are seeking dental care at an unprecedented and growing rate. Chronic disease and infirmity that accompany advanced age make dental care more challenging for this group. Dentists and their staff will need to continuously undertake educational opportunities that will foster and maintain their facility in providing care to the elderly. They will need to do this because Americans of advanced age are becoming the dominant age group seeking, and able to pay for, sophisticated dental services. The blend of those services is shifting away from removable prostheses to a rising demand for restorative, periodontic, and endodontic care. Root caries, in particular, will be a growing challenge to both providers and patients. There is mounting evidence oral disease impacts endocrine, cardiovascular, and pulmonary health, particularly in frail elders, and will likely provide many elderly additional stimuli to seek dental care. Providers who seek an alternative approach for delivering their services will find growing demand for and satisfaction with traveling to patients, rather than the other way around.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".