Association of Homelessness with COVID-19 Positivity among Individuals Visiting a Testing Centre: A Cross-Sectional Study
Bibliographic record
Abstract
Among those visiting a testing centre in Toronto, ON, between March and April 2020, people experiencing homelessness (n = 214) were more likely to test positive for COVID-19 compared with those not experiencing homelessness (n = 1,836) even after adjustment for age, sex and medical co-morbidity (15.4% vs. 6.7%, p < 0.001; odds ratio [OR] 2.41, 95% confidence interval [CI: 1.51, 3.76], p < 0.001). RésuméParmi ceux qui ont visité un centre de dépistage à Toronto, en Ontario, entre mars et avril 2020, les personnes en situation d'itinérance (n = 214) étaient plus susceptibles d'être testées positives à la COVID-19 que celles qui ne sont pas en situation d'itinérance (n = 1 836), même après ajustement selon l'âge, le sexe et la comorbidité (15,4 % c. 6,7 %, p < 0,001 ; rapport des cotes [RC] 2,41, intervalle de confiance à 95 % [IC : 1,51, 3,76], p < 0,001).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".