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River and estuary movements of yellow‐stage American eels<i>Anguilla rostrata</i>, using a hydrophone array

2010· article· en· W2095962283 on OpenAlexaffabout
Richard D. Hedger, Julian J. Dodson, Daniel Hatin, François Caron, Denis Fournier

Bibliographic record

VenueJournal of Fish Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReproductive biology and impacts on aquatic species
Canadian institutionsMinistère des Ressources naturelles et des Forêts (Québec)Université Laval
Fundersnot available
KeywordsEstuaryAnguilla rostrataBayFisheryOceanographyHabitatFish <Actinopterygii>NocturnalEnvironmental scienceBiologyEcologyGeology

Abstract

fetched live from OpenAlex

Patterns of summertime movement and habitat use of yellow-stage American eels Anguilla rostrata within York River and estuary and Gaspé Bay (Gaspesia, Québec, Canada) were examined using acoustic telemetry. Fifty fish were tagged with acoustic transmitters and released, either in the river or in the upper estuary, and their patterns of movement and habitat use were monitored at short spatial and temporal scales during the summer months using a dense hydrophone array. Approximately half of the fish released in the river swam to the estuary; two-thirds of the fish released within the estuary did not move out of the estuary. Anguilla rostrata were detected more frequently and had a greater areal range of detections during night, suggesting greater nocturnal activity. Longitudinal movements within the estuary tended to occur nocturnally, with upstream movements from early to late evening, and downstream movements from late evening to early morning. Approximately one-third of fish showed a regular pattern of movement, tending to reside in the deeper, downstream part of the estuary during day and in the shallower, more upstream part of the estuary during night. Approximately a quarter of fish, located in the upper estuary, remained upstream during both night and day. The remaining fish showed patterns intermediate between these two.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.448

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)0.0000.000

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 head0.012
GPT teacher head0.277
Teacher spread0.266 · 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 designBench or experimental
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

Citations38
Published2010
Admission routes2
Has abstractyes

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