Spatial variation in trophic structure of nearshore fishes in Lake Michigan as it relates to water clarity
Bibliographic record
Abstract
Nearshore water clarity, as measured by remotely sensed Kd(490), and stable C and N isotopes of several nearshore fishes differed across the Lake Michigan basin. Values of δ13C of round goby (Neogobius melanstomus), yellow perch (Perca flavescens), and spottail shiner (Notropis hudsonis) were depleted in the southeast where water clarity was low relative to the southwest where water clarity was greater. Bayesian analyses were used to evaluate spatial variation in diet composition and quantify the relationship between water clarity and the proportional importance of pelagic energy in fish diets. Water clarity in nearshore areas is likely related to variable riverine inputs, resuspension, and upwelling processes. While these processes may not directly impact δ13C or δ15N of nearshore fishes, we hypothesize that water clarity differentially affects benthic and pelagic algal production. Lower water clarity in the benthos and subsequently lower benthic productivity may be related to regional diet differences and increased reliance on pelagic energy sources. Mobile fishes such as alewife (Alosa pseudoharengus) may not be in isotopic equilibrium with regional prey sources and depart from spatial patterns observed in other nearshore fishes.
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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".