Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Adequate hand hygiene is often considered as the most effective method of reducing the rates of hospital-acquired infections, which are one of the major causes of increased cost, morbidity, and mortality in healthcare. Electronic monitoring technologies provide a promising direction for achieving sustainable hand hygiene improvement by introducing the elements of automated feedback and creating the possibility to automatically collect individual hand hygiene performance data. The results of the multiphase testing of an automated hand hygiene reminding and monitoring system installed in a complex continuing care setting are presented. The study included a baseline Phase 1, with the system performing automated data collection only, a preintervention Phase 2 with hand hygiene status indicator enabled, two intervention Phases 3 and 4 with the system generating hand hygiene reminding signals and periodic performance feedback sessions provided, and a postintervention Phase 5 with only hand hygiene status indicator enabled and no feedback sessions provided. A significant increase in hand hygiene performance observed during the first intervention Phase 3 was sustained over the second intervention Phase 4, with the postintervention phase also indicating higher hand hygiene activity rates compared with the preintervention and baseline phases. The overall trends observed during the multiphase testing, the factors affecting acceptability of the automated hand hygiene monitoring system, and various strategies of technology deployment are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it