Electronic tags and genetics explore variation in migrating steelhead kelts (Oncorhynchus mykiss), Ninilchik River, Alaska
Bibliographic record
Abstract
Acoustic and archival tags examined freshwater and marine migrations of postspawn steelhead kelts ( Oncorhynchus mykiss ) in the Ninilchik River, Alaska, USA. Postspawn steelhead were captured at a weir in 2002–2005. Scale analysis indicated multiple migratory life histories and spawning behaviors. Acoustic tags were implanted in 99 kelts (2002–2003), and an array of acoustic receivers calculated the average speed of outmigration, timing of saltwater entry, and duration of residency in the vicinity of the river mouth. Ocean migration data were recovered from two archival tags implanted in kelts in 2004 (one male and one female). Archival tags documented seasonal differences in maximum depth and behavior with both fish spending 97% of time at sea <6 m depth (day and night). All study fish were double tagged with passive integrated transponder (PIT) tags implanted in the body cavity. Less than 4% of PIT tags were retained in postspawn steelhead. Molecular genetics demonstrated no significant differences in genetic population structure across years or among spawning life history types, suggesting a genetically panmictic population with highly diverse life history characteristics in the Ninilchik River.
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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".