Bibliographic record
Abstract
Background. Physical function is an important measure of success of many medical and surgical interventions. Ability to adjust for comorbid disease is essential in health services research and epidemiological studies. Prior comorbidity indices, however, have been developed and designed to predict mortality, administrative outcomes, or for use in specific populations only. Research design. Diagnoses for inclusion in the index were generated through a review of the literature (including prior indices), and focus groups of patients, physicians, nurses, and rehabilitation therapists. The index was developed using two databases: A cross-sectional, simple random sample of Canadian adults and a sample of US adults seeking treatment for spine ailments. Subjects. The mean age of the 9,423 Canadian adults was 62.1 years (range 25--103; +/-SD 13.4) with a mean of 1.68 comorbid illnesses (SD +/- 1.65). The 28,349 US adults had a mean age of 49.0 years (range 18--97; +/-SD 15.3) and a mean of 1.71 (SD +/- 1.87) comorbidities. The databases were significantly different on all key variables including mean age, number of males and females, physical function scores and number of comorbid illnesses (p
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 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".