Determinants associated with receiving a medical appointment through the primary care access points for unattached adults in Quebec: A cross-sectional study
Bibliographic record
Abstract
Canada is experiencing an unprecedented primary care crisis, with 6.5 million Canadians reporting lacking a family physician, including 31% of the Quebec population. To address this problem, the province of Quebec implemented primary care access points (in French, they are Guichets d’accès à la première ligne , or GAPs) to help unattached patients navigate and access primary care services while awaiting attachment. We aimed to examine the determinants associated with unattached patients receiving a medical appointment compared to another service through the GAP. Cross-sectional data (n = 13,291) from two GAPs were collected (June 2022 to March 2023). Multivariable logistic regression was carried out. Being younger, calling for an acute health problem, medication renewal or to have administrative documentation filled, having a physical or mental health problem, and using GAP A (compared to GAP B) were associated with an increased likelihood of receiving a medical appointment. This study is the first to document the characteristics of patients using the GAP and their needs.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".