Evaluation of IFN-γ ELISA assays for quantifying interferon-gamma in Canadian bison
Bibliographic record
Abstract
was distributed to 385 clinical employees, including physicians, pharmacists, nurses, and lab specialists.Descriptive statistics and non-parametric tests (Mann-Whitney and Kruskal-Wallis) analyzed 5-point Likert scale (1 = Strongly Disagree, 2 = Partially Disagree, 3 = Neutral, 4 = Partially Agree, 5 = Strongly Agree) survey data, comparing median scores across ASP elements and employee groups, with significance at P < 0.05.Qualitative data from semi-structured interviews were thematically analyzed using NVIVO software.Results: Document reviews showed that ASPs at EHS hospitals are centrally managed, with all 12 hospitals meeting most core elements (Mode = 3).Variability in median scores highlighted challenges in formalizing programs across facilities.Survey results indicated partial dissemination of all core elements (median = 4).Leadership commitment (mean = 4.41, SD + 1.04) and pharmacy expertise (mean = 3.93, SD + 1.09) showed higher scores compared to other elements.Significant differences were observed between ASP members and non-members (p < 0.05), trained and untrained employees (p < 0.001), and across hospitals (p = 0.032).Qualitative analysis revealed strong strategic commitment and facility-driven ASP implementation supported by collaborative leadership, tailored education, and provider engagement.Key barriers included a lack of trust in ASP teams, physician resistance, absence of a competency framework, inadequate professional training, and limited access to rapid diagnostics.Discussion: Despite structural barriers and variability in adoption, EHS demonstrates strong leadership commitment, pharmacist engagement, and strategic implementation of ASP interventions.This first mixed-methods study in the UAE, utilizing data triangulation, benchmarks ASP practices against CDC standards.Findings align with practices in non-EHS government hospitals and high-income countries like Norway and Germany but contrast with some MENA region trends.Conclusion: EHS has established a robust foundation for sustainable ASPs, evidenced by adequate adoption and alignment with international frameworks.This study contributes to regional ASP benchmarking and highlights the need for further research to evaluate cost-effectiveness and clinical outcomes, including reductions in mortality and morbidity.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".