Air breathing in Magadi tilapia <i>Alcolapia grahami</i>, under normoxic and hyperoxic conditions, and the association with sunlight and reactive oxygen species
Bibliographic record
Abstract
Observations of the Magadi tilapia Alcolapia grahami in hot, highly alkaline Lake Magadi revealed that they air breathe not only during hypoxia, as described previously, but also during normoxia and hyperoxia. Air breathing under these latter conditions occurred within distinct groupings of fish (pods) and involved only a small proportion of the population. Air breathing properties (duration and frequency) were quantified from video footage. Air breathing within the population followed a diel pattern with the maximum extent of pod formation occurring in early afternoon. High levels of reactive oxygen species (ROS) in the water may be an irritant that encourages the air-breathing behaviour. The diel pattern of air breathing in the field and in experiments followed the diel pattern of ROS concentrations in the water which are amongst the highest reported in the literature (maximum daytime values of 2.53 – 8.10 μM H₂O₂). Interlamellar cell masses (ILCM) occurred between the gill lamellae of fish from the lagoon with highest ROS and highest oxygen levels, while fish from a normoxic lagoon with one third the ROS had little or no ILCM. This is the first record of air breathing in a facultative air-breathing fish in hyperoxic conditions and the first record of an ILCM in a cichlid species.
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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 | 0.000 |
| 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".