Eye lenses reveal ontogenetic trophic and habitat shifts in an imperiled fish, Clear Lake hitch (<i>Lavinia exilicauda chi</i>)
Bibliographic record
Abstract
Stable isotopes recorded in fish eye lenses are an emerging tool to track dietary shifts coincident with use of diverse habitats over the lifetime of individuals. Eye lenses are metabolically inert, sequentially deposited, archival tissues that can open avenues to chronicle contaminant exposures, diet histories, trophic dynamics and migratory histories of individual fishes. In this study, we demonstrated that trophic histories reconstructed using eye lenses can resolve key uncertainties regarding diet and trophic habitat shifts. Clear Lake hitch (Lavinia exilicauda chi), a threatened cyprinid, inhabits a single lake (Clear Lake, Lake County, California) and utilizes tributary streams for reproduction. Bayesian mixing models applied to δ13C and δ15N recorded in eye lenses uncovered ontogenetic diet shifts that corresponded with shifts in occupation of habitats providing spawning (tributary streams), rearing (littoral lake), and growth (pelagic lake) functions. The reconstruction of size-structured trophic and habitat information can provide vital information needed to manage and conserve imperiled species such as the Clear Lake hitch.
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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".