Characterisation of putative oxygen chemoreceptors in bowfin (<i>Amia calva</i>)
Bibliographic record
Abstract
Serotonin containing neuroepithelial cells (NECs) are putative oxygen sensing cells found in different locations within the gills of fish. In this study we wished to determine the effect of sustained internal (blood) hypoxaemia versus external (aquatic) hypoxia on the size and density of NECs in the first gill arch of bowfin (Amia calva), a facultative air breather. We identified five different populations of serotonergic NECs in this species (Types I-V) based on location, presence of synaptic vesicles (SV) that stain for the antibody SV2, innervation and labelling with the neural crest marker HNK-1. Cell Types I-III were innervated, and these cells, which participate in central O2 chemoreflexes, were studied further. Although there was no change in the density of any cell type in bowfin after exposure to sustained hypoxia (6.0 kPa for 7 days) without access to air, all three of these cell types increased in size. In contrast, only Type II and III cells increased in size in bowfin exposed to sustained hypoxia with access to air. These data support the suggestion that NECs are putative oxygen-sensing cells, that they occur in several locations, and that Type I cells monitor only hypoxaemia, whereas both other cell types monitor hypoxia and hypoxaemia.
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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".