Additional file 3 of Veterinarian barriers to knowledge translation (KT) within the context of swine infectious disease research: an international survey of swine veterinarians
Bibliographic record
Abstract
Additional file 3: Table 1. Demographics (%) of survey respondent by self-identified veterinary role. Figure 1. Demographic composition by role (%) of survey respondents versus the AASV membership. Table 2A. Summary of post hoc grouping of the multiple response options for each survey question into dichotomous responses for analysis (used in calculation of all prevalence ratios). Table 2B. Self-reported veterinary role as practitioner or non-practitioner versus dichotomized role. Table 2C. Self-reported veterinary role versus sows worth of veterinary oversight. Table 2D. Dichotomized veterinary role versus sows worth of veterinary oversight. Table 3. Dichotomised responses* for reported level of process efficiency (Q8) and level of process stress with staying current (Q9) versus role (direct vs. indirect). Table 4. (Q10) Self-reported familiarity with epidemiologic and evidence based terminology, by role. Response options not dichotomized (i.e the same information but dichotomized responses only are shown in Table 3 of main body of manuscript). Table 5. (Q12) Self -reported level of confidence to assess aspects of a research paper, by role (direct vs. indirect). Table 6A. (Q12) Self -reported level of confidence to assess aspects of a research paper, by role (direct vs. indirect) with responses dichotomized* as ‘Confident’ or ‘No Confidence/Do not evaluate’. Table 6B. (Q12) Association of having confidence* with usually reading* versus not usually reading the methods section of journal articles. Table 7. (Q4) Ranking of first (1st), second (2nd), and third (3rd) choices for getting more information for difficult clinical cases, by role (direct vs. indirect). Table 8. (Q11) Self-reported frequency of reading sections of scientific journal articles, by role. Table 9. Self-reported scientific journal access (Q15) and article service awareness (Q17) by frequency of blocked access (Q16) (Often, Occasionally, Rarely, Not at all). Table 10. (Q18) Association of selection of a preferred reading material format (for keeping current with a specific infectious disease topic) with veterinary role. Table 11A. (Q18) Respondent self-reported time*(Q7), skill*(Q10,12) and access*(Q11) by their choice of individual primary research papers (IPRP) as a preferred reading format for keeping current with a specific disease topic (IPRP not selected vs IPRP selected). Table 11B. (Q18) Association of time, skill and access for respondents with not selecting IPRP* versus selecting IPRP as a preferred reading format. Table 12. (Q18) Association of selected combinations of choices* of reading material format options with direct† veterinary role versus indirect†† veterinary role.
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How this classification was reachedexpand
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 | 0.021 |
| 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) | 0.730 | 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 teacher head, 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".