Bibliographic record
Abstract
In Canada there has recently been increased public and political debate surrounding the reasons for the continued overcrowding seen in hospital emergency rooms (ERs) around the country. One theory is that ER overcrowding is due to a shortage of family physicians (GP). The theory goes that if patients have medical problems and no GP, they will go to an ER in order to receive treatment contributing to overcrowding. The question then is whether or not ERs have become substitute GPs? Only a historical analysis can answer this question. While many opinions exist on the subject no attempts have actually been made to correlate the number of GPs with ER use through time. Data was obtained from: hospital archives, Kingston Public Library Special Collections, Statistics Canada and the Ontario Physicians Human Resource Database on the number of ER visits and the number of GPs in the city of Kingston, Ontario, from 1961 to 2006. Regression analysis was used to look for a correlation between the number of GPs in Kingston and the number of ER visits over the past fourty-five years. The population of Kingston during this time period was used as a controlling variable. Regression analysis showed that there was a historical correlation between the number of ER visits and the number of GPs in Kingston. Therefore, it appears that GPs have spared the ER from overcrowding.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".