Bibliographic record
Abstract
The purpose of this study was to identify the factors affecting the use of superior general hospitals on public holidays by using the medical use model (Dutton ''s medical use model) with the medical panel data. The study found that 34.2% of superior general hospital emergency rooms were used on public holidays and the factors which made statistically significant influences on the use of superior general hospital emergency rooms on public holidays were whether patients were operated or emergency care and inspection etc. Also, there was a difference depending on whether the type of establishment of the medical insititution is national or private. In other words, patients who received emergency care and examinations were found to make more frequent visit to hospital emergency room on pubic holiday ,compared to patients who underwent surgery and those who visited emergency rooms in the private superior general hospital did so, compared to those who visited emergency room in the national general hospital(OR, 4.4, 3.386, respectively). Therefore, it is necessary to consider the introduction of integrated care of health and social care medical service that focuses on primary care in Denmark, which focuses on patients, and pre-The Canadian Triage and Acuity Scale(pre-CTAS) in the UK.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".