Rat cardiovascular telemetry: Marginal distribution applied to positive control drugs
Bibliographic record
Abstract
Cardiovascular effects are considered frequent during drug safety testing. This investigation aimed to characterize the pharmacological response of the conscious telemetered rat in vivo model to known cardiovascular active agents. These effects were analyzed using statistical analysis and cloud representation with marginal distribution curves for the contractility index and heart rate as to assess the effect relationship between cardiac variables. Arterial blood pressure, left ventricular pressure, electrocardiogram and body temperature were monitored. The application of data cloud with marginal distribution curves to heart rate and contractility index provided an interesting tactic during the interpretation of drug-induced changes particularly during selective time resolution (i.e. marginal distribution curves restricted to Tmax). Taken together, the present data suggests that marginal distribution curves can be a valuable interpretation strategy when using the rat cardiovascular telemetry model to detect drug-induced cardiovascular effects. Marginal distribution curves could also be considered during the interpretation of other inter-dependent parameters in safety pharmacology studies.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".