Antibiotic prescription patterns amongst children residing in remote Northern Manitoba communities
Bibliographic record
Abstract
In recent years, there has been growing concerns with respect to health care providers in relation to over-prescription of antibiotics in a primary care setting, compounding the rising concerns of antibiotic resistance. There currently is a deficit in the literature with respect to prescription patterns being quantified and reported as it pertains to children and adolescents residing in remote northern Manitoba communities. We sought to address this discrepancy in the literature via evaluating trending data regarding antibiotic prescription patterns in select remote northern communities in Manitoba in children aged 0 to 19. We attempted to address this discrepancy in the literature via evaluating trending data regarding antibiotic prescription patterns in select remote northern communities in Manitoba in children aged 0 to 19. Our results show preliminary evidence of decreasing rates of antibiotic prescriptions in remote northern Manitoba communities. More work is necessary to get a broader picture of past and current antibiotic prescription patterns in order to serve as a catalyst for clinical guideline reforms when necessary, to give us a better picture of the overall quality of care these patients receive and ultimately to improve the health outcomes of patients in these communities
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".