Bibliographic record
Abstract
the front door of the healthcare system (Kiran 2022). Defined more than 30 years ago, primary care is a model of healthcare that includes first-contact care, continuity of care, comprehensiveness and coordination (Starfield 1994). For a patient, it is their entry point to the rest of the healthcare system, and ideally, the place where they go to have most of their healthcare needs met by the same provider over time. Primary care is a component of primary healthcare, which is a broader approach that includes public health as well as policy, action and empowerment strategies involving multiple sectors (WHO n.d.). While Canada has made improvements in primary care delivery, its performance still lags behind that of other countries (Duong and Vogel 2023). One of its shortfalls is accessibility. More than 6.5 million people in Canada do not have access to primary care (Duong and Vogel 2023). This is concerning, and even more so because the population is aging, and many people have one or more chronic illnesses needing ongoing follow-up (Public Health Agency of Canada 2022) and social determinants of health requiring action (Andermann et al. 2016).
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 | 0.009 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.105 | 0.085 |
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".