Bibliographic record
Abstract
legal rights, dignity, autonomy, quality of life, and quality of care of elders. It carries out this mission through research, policy development, technical assistance, advocacy, education, and training. The ABA Commission consists of a 15-member interdisciplinary body of experts in aging and law, including lawyers, judges, health and social services professionals, academics, and advocates. With its professional staff, the ABA Commission examines a wide range of law-related issues, including: legal services to older persons; health and long-term care; housing needs; professional ethical issues; Social Security, Medicare, Medicaid, and other public benefit programs; planning for incapacity; guardianship; elder abuse; health care decision-making; pain management and end-of-life care; dispute resolution; and court-related needs of older persons with disabilities. About the American Psychological Association The American Psychological Association (APA) is the largest scientific and professional organization representing psychology in the United States and is the world’s largest association of psychologists. Through its divisions in 53 subfields of psychology and affiliations with 59 state, territorial, and Canadian provincial associations, APA works to advance psychology as a science, as a profession, and as a means of promoting health, education, and human welfare. The APA Office on Aging coordinates the association’s activities pertaining to aging and geropsychology (the field within psychology devoted to older adult issues). The Committee on Aging (CONA) is the committee
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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.060 | 0.021 |
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".