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
Nurses are involved in many of the painful procedures performed on hospitalized children. In collaboration with physicians, nurses have an exceptional responsibility to have knowledge to manage the pain; however, the evidence indicates this is not being done. Issues may be twofold: (a) opportunities to improve knowledge of better pain care practices and/or (b) ability to use knowledge. Empirical evidence is available that if used by health care providers can reduce pain in hospitalized children. Theory-guided interventions are necessary to focus resources designated for learning and knowledge translation initiatives in the area of pain care. This article presents the Knowledge Use in Pain Care (KUPC) conceptual model that blends concepts from the fields of knowledge utilization and work life context, which are believed to influence the translation of knowledge to practice. The four main components in the KUPC model include those related to the organization, the individual nurse, the individual patient, and the sociopolitical context. The KUPC model was conceptualized to account for the complex circumstances surrounding nurse's knowledge uptake and use in the context of pain care. The model provides a framework for health care administrators, clinical leaders, and researchers to consider as they decide how to intervene to increase knowledge use to reduce painful experiences of children in the hospital.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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