Bibliographic record
Abstract
Insulin is a key hormone for the regulation of metabolism in vertebrates. Insulin is produced by pancreatic islet cells in response to elevated glucose levels and leads to the uptake of glucose by tissues such as liver and adipose tissue to store energy. Insulin also has additional functions in regulating development. Previous work has shown that the proglucagon gene, which encodes hormones counter regulating insulin, is duplicated in teleost fish, and that the peptide hormones encoded by these genes have diversified in function. I sought to determine whether similar processes have occurred to insulin genes in these species. Searches of fish genomes revealed an unexpected diversity of insulin genes. A triplication of the insulin gene occurred at the origin of teleost fish, however one of these three genes, insc, has been lost in most teleost fish lineages. The two other insulin genes, insa and insb, have been retained but show differing levels of selective constraint suggesting that they might have diversified in function. Intriguingly, a duplicate copy of the insa gene, which I named insab, is found in many fish. The coding sequence encoded by insab genes is under weak selective constraint, with its predicted protein sequences losing their potential to be processed into a two-peptide hormone. However, these sequences have retained perfectly conserved cystine residues, suggesting that they maintain insulin's three-dimensional structure and therefore might modulate the processing and secretion of insulin produced by the other genes.
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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 | 0.001 | 0.001 |
| 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".