Bibliographic record
Abstract
OBJECTIVE: To estimate the impact of the coronavirus disease 2019 (COVID-19) pandemic on FP finances in Alberta. DESIGN: A financial model that included fees, visits per day, number of days of practice, and overhead costs. SETTING: Alberta before, during, and after the COVID-19 pandemic. PARTICIPANTS: Hypothetical fee-for-service FP practices. INTERVENTIONS: Changes in practice modes caused by the pandemic and changes to fees set by the Government of Alberta (no interventions were controlled by the researchers). MAIN OUTCOME MEASURES: Annual average FP billings and annual average FP income after overhead expenses. RESULTS: Practice changes related to COVID-19 could result in a reduction in average FP income (billings after expenses) of 27% to 78%. CONCLUSION: Practice pattern changes, including the rapid adoption of telemedicine owing to the COVID-19 pandemic, will reduce incomes for fee-for-service community FP practices in Alberta. Fees at current levels could make some practices unsustainable.
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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 | 0.001 |
| 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) | 0.000 | 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".