Getting to the heart of anatomical diversity and phenotypic plasticity: fish hearts are an optimal organ model in need of greater mechanistic study
Bibliographic record
Abstract
Natural selection has produced many vertebrate 'solutions' for the cardiac life-support system, especially among the approximately 30,000 species of fishes. For example, across species, fish have the greatest range for central arterial blood pressure and relative ventricular mass of any vertebrate group. This enormous cardiac diversity is excellent ground material for mechanistic explorations. Added to this species diversity is the emerging field of population-specific diversity, which is revealing that cardiac design and function can be tailored to a fish population's local environmental conditions. Such information is important to conservation biologists and ecologists, as well as physiologists. Furthermore, the cardiac structure and function of an individual adult fish are extremely pliable (through phenotypic plasticity), which is typically beneficial to the heart's function when environmental conditions are variable. Consequently, exploring factors that trigger cardiac remodelling with acclimation to new environments represents a marvellous opportunity for performing mechanistic studies that minimize the genetic differences that accompany cross-species comparisons. What makes the heart an especially good system for the investigation of phenotypic plasticity and species diversity is that its function can be readily evaluated at the organ level using established methodologies, unlike most other organ systems. Although the fish heart has many merits as an organ-level model to provide a mechanistic understanding of phenotypic plasticity and species diversity, bringing this potential to fruition will require productive research collaborations among physiologists, geneticists, developmental biologists and ecologists.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".