Upper thermal tolerance of closely related <i>Danio</i> species
Bibliographic record
Abstract
The main finding of this study was that measuring maximum heart rate during incremental warming was an effective tool to estimate upper thermal limits in three small cyprinid Danio species, which differed significantly. Arrhenius breakpoint temperature for maximum heart rate, purportedly an index of optimum temperature, was 21·2 ± 0·4, 20·1 ± 0·4 and 18·9 ± 0·8° C (mean ± s.e.) for zebrafish Danio rerio, pearl danio Danio albolineatus and glowlight danio Danio choprae, respectively. The temperature where cardiac arrhythmias were first induced during warming (T(arr)) was 36·6 ± 0·7, 36·9 ± 0·8 and 33·2 ± 0·8° C (mean ± s.e.) and critical thermal maximum (T(Cm)) was 39·9 ± 0·1, 38·9 ± 0·1 and 37·2 ± 0·1° C (mean ± s.e.) for D. rerio, D. albolineatus and D. choprae, respectively. The finding that T(arr) was consistently 3-4° C lower than T(Cm) suggests that collapse of the cardiac life support system may be a critical trigger for upper temperature tolerance. The upper thermal limits established here, which correlate well with a broad natural environmental temperature range for D. rerio and a narrow one for D. choprae, suggest that upper thermal tolerance may be a genetic trait even among closely related species acclimated to common temperatures.
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 | 0.000 | 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 | 0.001 |
| 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".