A simple descriptive analysis of hospital admissions’ progress: a case study of the Greatest Public Gene- ral Hospital, Athens, Greece
Bibliographic record
Abstract
This paper studies the progress of hospital admissions over the time period 1995-2005 for the largest Greek general public hospital. Daily admissions data, disaggregated into elective and emergency were collected from the IT Department of the hospital. Great seasonality for hospital admissions was found. They reduce during weekends, the summer months and official holidays. Emergency admissions are at their peak in the beginning of the week and decline afterwards. During weekends, emergency admissions decrease by 25%. The majority of hospital elective admissions enter into the hospital from Monday to Thursday. During Friday and weekends, elective hospital admissions fall sharply, by 63%. However, on Sunday, they slightly increase. The mean number of total hospital admissions increased by 17% from 1995 to 2005. This increase in total admissions results from the significant increase of elective admissions (by 56%) and not from the emergency admissions that fell by 17%.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".