An Assessment of Large-Volume Infusion Device Use by Nurses in Preparation for Conversion to Dose Error-Reduction Software
Why this work is in the frame
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Bibliographic record
Abstract
In 2008, the Corporate Pharmacy of the Interior Health Authority of British Columbia, Canada embarked on a project to replace large-volume (LV) infusion devices with "smart pumps" (infusion devices equipped with dose error-reduction systems [DERS]). To determine ideal device-to-patient ratios for procurement, Interior Health performed a research study to investigate infusion practice and LV device use. Discoveries were made regarding device use and perceptions of nurses regarding infusion administration, policy, and asset management that have aided in successful device implementation and will aid in future optimization of safe infusion therapy. Since 2009, Interior Health has completed implementation of DERS-equipped LV infusion devices in its acute care facilities.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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