Use of 2 sedation protocols to successfully validate a sedation assessment scale in bearded dragons (Pogona vitticeps)
Bibliographic record
Abstract
Objective: To validate a sedation assessment scale by evaluating 2 sedation protocols in bearded dragons. Methods: In a randomized, blinded, crossover study, 10 bearded dragons were sedated IM with dexmedetomidine (0.1 mg/kg) and methadone (2 mg/kg; DM), and dexmedetomidine (0.1 mg/kg), methadone (2 mg/kg), and ketamine (10 mg/kg; DMK). Sedation assessment was performed with video recording at baseline (T0) and every 5 minutes from 10 to 60 minutes after injection (T10 to T60). After T60, atipamezole (1 mg/kg) was given IM. Behaviors used to assess sedation in several species were tested. Construct validity (ie, does a scale measure what is intended) was evaluated by comparing sedation scores over time using the Friedman and Dunn post hoc tests and between treatments, using a Mann-Whitney test. Scores of 25 videos randomly selected from a total of 216 recorded videos were used to calculate intra- and inter-rater reliability using the intraclass correlation coefficient. Internal consistency was calculated using the Cronbach α coefficient. Results: Data from a pilot animal (DM) and a misinjection (DMK) were excluded. No adverse events were observed. Six out of 10 evaluated items were selected for the sedation scale. Sedation scores were higher with DMK than DM (T10 to T60). The intraclass correlation coefficient > 0.81 for all raters indicates "very good" intra-rater (95% CI, 0.66 to 1) and inter-rater (95% CI, 0.71 to 1) reliability. Internal consistency was "excellent" (α = 0.904). Conclusions: Deep sedation occurred with DMK but not DM. The sedation scale demonstrated validity, responsiveness, and reliability. Clinical Relevance: The validated sedation scale aids consistency in evaluating sedation in bearded dragons.
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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".