Evaluation of postmortem changes in tissue structure in the bottlenose dolphin (<i>Tursiops truncatus</i>)
Bibliographic record
Abstract
Postmortem changes in geometry, density, and sound speed within organs and tissues (melon, bone, blubber, and mandibular fat) of the dolphin head were evaluated using computed tomography (CT) scans of live and postmortem bottlenose dolphins (Tursiops truncatus). Specimens were classified into three different treatment groups: live, recently dead, and frozen followed by thawing. Organs and tissues in similar anatomical regions of the head were compared in CT scans of the specimens to identify postmortem changes in morphology. In addition, comparisons of Hounsfield units in the CT scans were used to evaluate postmortem changes in the density of melon, bone, blubber, and mandibular fat. Sound speed measurements from melon, blubber, connective tissue, and muscle were collected from fresh and frozen samples in the same specimen to evaluate effects due to freezing and thawing process on sound speed measurements. Similar results in tissue and organ geometry, density, and sound speed measurements suggested that postmortem material is a reliable approximation for live melon, bone, blubber, muscle, connective tissue, and mandibular fat. These results have implications for examining viscoelastic properties and the accuracy of simulating sound transmission in postmortem material.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".