Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PRACTICAL RELEVANCE: Many of the changes that occur with aging are not considered pathologic and do not negatively affect overall wellness or quality of life. Ruling out disease is essential, however, when attempting to determine whether an aged cat can be considered 'healthy'. A clear understanding of the normal and abnormal changes that are associated with aging in cats can help practitioners make decisions regarding medical management, feeding interventions and additional testing procedures for their aged patients. CLINICAL CHALLENGES: It can be difficult to determine if a cat is displaying changes that are appropriate for age. For example, healthy aged cats may have hematologic or serum biochemistry changes that differ from those of the general feline population. Assessment of behavioral health and cognitive changes, as well as auditory, olfactory and visual changes, can also be challenging in the aged patient. GOALS: This is the second of two review articles in a Special Issue devoted to feline healthy aging. The goals of the project culminating in these publications included developing a working definition for healthy aging in feline patients and identifying clinical methods that can be used to accurately classify healthy aged cats. This second review proposes criteria for assessing 'healthy aged cats'. EVIDENCE BASE: There is a paucity of research in feline aging. The authors draw on expert opinion and available data in both the cat and other species.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it