Additional file 1 of The dose-response relationship between socioeconomic deprivation and alcohol-attributable mortality risk—a systematic review and meta-analysis
Bibliographic record
Abstract
Additional file 1: The dose-response relationship between socioeconomic deprivation and alcohol-attributable mortality risk – a systematic review and meta-analysis includes Tables S1 to S10, Text S1, and Fig. S1. Table S1 PRISMA 2009 checklist. Text S1. Search terms. Table S2. Inclusion criteria. Table S3. Diagnoses 100% attributable to alcohol use with ICD-10 codes. Table S4. Diagnoses with an alcohol-attributable fraction > 10% for mortality globally as per the Global Status Report on Alcohol and Health, 2018 (100% attributable causes are excluded from this table and shown in Table S3). Table S5 Quality assessment criteria and ratings. Table S6. Quality checklist. Ratings on population representativeness of the sample, measurement of socioeconomic status (SES), operationalization of alcohol-attributable mortality, data linkage, and age-adjustment for each study included in the meta-analysis. Table S7. Results from random-effects meta-regression models predicting the relative risk (RR). Table S8. Results from permutation tests to test the robustness of random-effects meta-regression models predicting the log relative risk (RR) conditional on the level of socioeconomic deprivation, the indicator of socioeconomic status (SES) used, and sex in three consecutive models, while controlling for clustering of estimates within studies. Table S9. Results from one-stage random-effects dose-response meta-analyses on the relative mortality risk for alcohol-attributable mortality conditional on the level of socioeconomic deprivation, stratified by sex and indicator of socioeconomic status (SES). Fig. S1. Dose-response relationship between the level of socioeconomic deprivation and the relative risk of mortality from an alcohol-attributable cause of death (RR) by indicator of socioeconomic status (SES) and sex. Table S10. Results from sensitivity analyses. Random-effects meta-regression models predicting the log relative risk (RR) conditional on the study quality (a least one criterion not fulfilled vs. all criteria fulfilled), the country where the study was conducted (Finland vs. any other country), and the income inequality in the country (Gini coefficient).
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 | 0.006 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.795 | 0.040 |
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".