Linking environmental salinity to respiratory phenotypes and metabolic rate in fishes: a data mining and modelling approach
Bibliographic record
Abstract
The gill is the primary site of ionoregulation and gas exchange in adult teleost fishes. However, those characteristics that benefit diffusive gas exchange (large, thin gills) may also enhance the passive equilibration of ions and water that threaten osmotic homeostasis. Our literature review revealed that gill surface area and thickness were similar in freshwater (FW) and seawater (SW) species; however, the diffusive oxygen (O2) conductance (Gd) of the gill was lower in FW species. While a lower Gd may reduce ion losses, it also limits O2 uptake capacity and possibly aerobic performance in situations of high O2 demand (e.g. exercise) or low O2 availability (e.g. environmental hypoxia). We also found that FW fishes had significantly higher haemoglobin (Hb)-O2 binding affinities than SW species, which will increase the O2 diffusion gradient across the gills. Therefore, we hypothesized that the higher Hb-O2 affinity of FW fishes compensates, in part, for their lower Gd. Using a combined literature review and modelling approach, our results show that a higher Hb-O2 affinity in FW fishes increases the flux of O2 across their low-Gd gills. In addition, FW and SW teleosts can achieve similar maximal rates of O2 consumption (ṀO2,max) and hypoxia tolerance (Pcrit) through different combinations of Hb-O2 affinity and Gd. Our combined data identified novel patterns in gill and Hb characteristics between FW and SW fishes and our modelling approach provides mechanistic insight into the relationship between aerobic performance and species distribution ranges, generating novel hypotheses at the intersection of cardiorespiratory and ionoregulatory fish physiology.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".