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Divergent life histories among smallmouth bass <i>Micropterus dolomieu </i>inhabiting a connected river–lake system

2008· article· en· W2164159916 on OpenAlexaffabout
Brandon L. Barthel, Steven J. Cooke, Jana Svec, Cory D. Suski, Christopher M. Bunt, Frank J. S. Phelan, David P. Philipp

Bibliographic record

VenueJournal of Fish Biology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsMicropterusHabitatBass (fish)Nest (protein structural motif)BiologyReproductive successFisheryEcologySpawn (biology)CentrarchidaeEndangered speciesPopulationDemography

Abstract

fetched live from OpenAlex

Annual reproductive surveys monitored nesting location, reproductive success and the age and size of individually tagged male smallmouth bass Micropterus dolomieu that reproduced in Millers Lake, a 45 ha widening of the Mississippi River, Ontario, and in a 1·5 km pool and riffle section of the river directly upstream. The vast majority of males displayed fidelity to either the river or the lake as reproductive habitat throughout their lifetimes. Nearly, half of the males that reproduced in successive years exhibited strong nest‐site fidelity by nesting within 20 m of their previous year’s nest site. In most years, when compared to those in the lake, reproductive males in the river differed significantly in reproductive characteristics including age and size at maturation and nesting success rates. A 3 year telemetry project identified two distinct habitat use patterns: lake‐resident fish remained in the lake throughout the year and potamodromous individuals migrated from the lake to upriver spawning habitat in the spring and then returned to the lake prior to the onset of winter. Integration of habitat use and reproductive data suggests that there are significant differences in the life‐history strategies of fish that reproduce in the river v. the lake.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.190
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations76
Published2008
Admission routes2
Has abstractyes

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