Short-term stress for long-lasting otolith morphology — brief embryological stress disturbance can reorient otolith ontogenetic trajectory
Bibliographic record
Abstract
Long-term plasticity of otolith shape has become a unifying principle to use morphological differences as indicator of environmental conditions. Contrary to the longstanding paradigmatic view that otolith shape can only reflect residency in particular environmental conditions over long time periods, data emphasize that otolith ontogenetic trajectory may be reoriented in case of short-term episodes of environmental disturbance during early lifetime. Using geometric morphometrics, discrimination was posible in absence of growth-related differences between control and brown trout (Salmo trutta Linnaeus, 1758) that have experienced brief thermal stress prior to their emergence but have grown in similar conditions (i.e., cohabiting within the same aquarium) during 6 months. Data emphasize that brief stress during key developmental periods can durably influence ontogenetic trajectories, subsequent otolith development, and can consequently change otolith morphology in juveniles. Therefore, differences in shape between groups of fish may not be exclusively indicative of long-time residency in contrasted and (or) separated habitats as it is generally assumed. Moving beyond long-term assumptions is fundamental if otolith shape is to be used as an effective tool for management of fisheries resources in the future.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".