Ecology of the Rio Grande Silvery Minnow (Cyprinidae: <b> <i>Hybognathus amarus)</i> </b> Inferred from Specimens Collected in 1874
Bibliographic record
Abstract
The Rio Grande silvery minnow (Hybognathus amarus) was historically an abundant and widespread species in the Rio Grande Basin. Its decline to endangered status had many probable causes and has spanned more than a century. Specimens of H. amarus collected in July 1874 at San Ildefonso, near Santa Fe, New Mexico, allowed a retrospective assessment of the ecology and morphology of the species and the environmental conditions of the Rio Grande in areas foraged by these minnows. Analysis of diatoms from the gut showed that H. amarus foraged mainly in nutrient-enriched areas on mud substrates in 1874 and to lesser extents on periphyton associated with plant, sand, and rock substrates. Gut contents included a considerable amount of fine-grained sediment and a wide variety of organic materials including detritus, pine pollen, cyanobacteria, algae, and diatoms. Scale annuli showed that H. amarus was once a relatively long-lived minnow; all age classes from 1 to 5 were present in 1874. The presence of multiple individuals of several ages suggested that annual survival rates were high historically and that the species may be iteroparous, rather than short-lived and semelparous as widely held. The morphology of H. amarus from a captive stock in 2003 was consistent with the morphology of the 1874 specimens.
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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 | 0.000 |
| 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".