Identifying river of origin for age-0 <i>Scaphirhynchus</i> sturgeons in the Missouri and Mississippi rivers using fin ray microchemistry
Bibliographic record
Abstract
Understanding linkages between natal and nursery habitats is critical for conservation of riverine fishes. Scaphirhynchus sturgeons inhabiting the middle Mississippi River may originate from the Missouri or Mississippi rivers, although relative importance of these recruitment sources is unknown. We characterized the relationship between water and sturgeon fin ray Sr:Ca, verified shifts in water Sr:Ca are recorded in age-0 sturgeon fin rays, and determined whether age-0 sturgeons from the Mississippi and Missouri rivers exhibited distinct fin ray Sr:Ca signatures. Fin ray Sr:Ca of laboratory-reared fish reflected transfer from water with elevated Sr:Ca to ambient water 1 day posthatch, indicating that short-term residency in environments can be detected. Nine of 30 age-0 fish captured in the middle Mississippi River were Missouri River emigrants. Four of these emigrants originated in the upper portion of the lower Missouri River (≥589 km upstream from its mouth), where water Sr:Ca is higher compared with the lowermost section of the Missouri River and the Mississippi River. Twenty-five of 30 fish collected from the lowermost section of the Missouri River originated within this river segment; the remainder originated upriver. Fin ray Sr:Ca enables identification of natal river segment for age-0 sturgeons and contributions of river segments to sturgeon recruitment.
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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".