Development and Validation of the Unesp-Botucatu Goat Acute Pain Scale
Bibliographic record
Abstract
We aimed to develop and validate the Unesp-Botucatu goat acute pain scale (UGAPS). Thirty goats (5 negative controls and 25 submitted to orchiectomy) were filmed for 7 min at the time points 24 h before and 2 h, 3 h (1 h after analgesia), and 24 h after orchiectomy. After content validation, according to an ethogram and literature, four blind observers analyzed the videos randomly to score the UGAPS, repeating the same assessment in 30 days. According to the confirmatory factor analysis, the UGAPS is unidimensional. Intra- and interobserver reliability was very good for all raters (Intraclass correlation coefficient ≥85%). Spearman's correlation between UGAPS versus VAS was 0.85 confirming the criterion validity. Internal consistency was 0.60 for Cronbach's α Cronbach and 0.67 for McDonald's ω. The item-total correlation was acceptable for 80% of the items (0.3-0.7). Specificity and sensitivity based on the cut-off point were 99% and 90%, respectively. The scale was responsive and demonstrated construct validity shown by the increase and decrease of scores after surgery pain and analgesia, respectively. The cut-off point for rescue analgesia is ≥3 of 10, with an area under the curve of 95.27%. The UGAPS presents content, criterion, and construct validities, responsiveness, and reliability to assess postoperative pain in castrated goats.
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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 | 0.001 | 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 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".