Spatial Ecology of Juvenile Muskellunge and Northern Pike in Upper St. Lawrence River Nursery Bays
Bibliographic record
Abstract
Nursery habitat requirements for age-0 Esox spp. in the upper St. Lawrence River are well understood; however, little is known about the influence of environmental variables (i.e., depth, temperature, habitat) on their spatiotemporal ecology during fall and winter periods.A hatchery study evaluated biologically relevant endpoints post-implantation of a mini-acoustic transmitter in age-0 Muskellunge.Neither tag expulsion nor mortality were observed, nor influence of tag presence on short-term growth rates.Applying this tool to evaluate their ecology, I captured and tagged age-0 Muskellunge (Esox masquinongy) and Northern Pike (Esox lucius) from August to October in natal bays.Detection data, modeled against environmental covariates, found deeper littoral regions were used by both species, and complex interactions between covariates influenced spatial trends during this critical period.With similar overwintering spatial ecology between these congeneric competitors, overwintering microhabitat use studies in association with water level management may confirm habitat overlap and inform wetland restoration efforts.Station.Thank you to Elodie Ledee for her down-to-earth attitude and continuous patience, educating me on data analysis and interpretation, and Jeremy Kerr for being a wonderful mentor.
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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".