Additional file 1 of Socioeconomic gradient in mortality of working age and older adults with multiple long-term conditions in England and Ontario, Canada
Bibliographic record
Abstract
Additional file 1: Supplementary Table 1. Health administrative data sources used (Ontario). Supplementary Table 2. Description of the 2015 Index of Multiple Deprivation (IMD) and 2016 ON-MARG material deprivation index (ON). Supplementary Table 3. Time criteria for long-term conditions counted in the current study (including those counted in the sensitivity analysis) in England. Supplementary Table 4: Case ascertainment algorithms for long-term conditions, applied to Ontario (Canada) health administrative data sources. Supplementary Table 5. Demographic characteristics of people with missing data that were excluded from the analytical sample by jurisdiction. Supplementary Table 6. Descriptive table of those censored in England and Ontario (Canada). Supplementary Table 7. Prevalence of long-term conditions by jurisdiction. Supplementary Table 8. Cox regression estimates for model 1 and 2 in England and Ontario (Canada). Supplementary Table 9. Cox regression estimates from model 3 and 4 stratified for working age adults (18–64 years) in England and Ontario (Canada). Supplementary Table 10. Cox regression estimates from model 3 and 4 stratified for older adults (65 + years) in England and Ontario (Canada). Supplementary Table 11. Cox Regression Estimates from the sensitivity analyses (to include the list of 26 conditions) of model 3 and 4 for working age adults (18–64 years) in England and Ontario (Canada). Supplementary Table 12. Cox Regression Estimates from the sensitivity analyses (to include the list of 26 conditions) of model 3 and 4 for older adults (65 + years) in England and Ontario (Canada).
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.581 | 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 teacher head, 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".