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Record W4254285070 · doi:10.47886/9781888569988.ch4

Burbot: Ecology, Management, and Culture

2008· book-chapter· en· W4254285070 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Fisheries Society eBooks · 2008
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatFisheryRange (aeronautics)PopulationGeographyFish <Actinopterygii>Home rangeEcologyEnvironmental scienceBiologyDemography

Abstract

fetched live from OpenAlex

Abstract.—Movements of 11 sonic tagged burbot &lt;em&gt;Lota lota &lt;/em&gt;were examined in the Kootenai River, Idaho, USA and Kootenay River and Kootenay Lake, British Columbia, Canada through up to three spawning seasons. Our objectives were to determine seasonal movements, differences in behavior of individual burbot, and the role of temperature and discharge on prespawn movement. Burbot demonstrated multiple movement patterns: 3 burbot were very mobile, 3 appeared to be intermediate in activity, and 5 were sedentary in summer, while 2 of the 11 entered Kootenay Lake and returned to the river. Most burbot began in autumn what may have been prespawn migrations when river temperatures fell to a range of 3.0–4.9°C. Six burbot entered the Goat River during the spawning season, of which five showed a multiple-year pattern of fidelity, and four returned to an apparent home pool and then exhibited sedentary behavior until the following winter. Three of the 11 burbot demonstrated an apparent nonspawning or rest year, but this was thought to be habitat-related. Logistic regression analysis of three of the six fish entering the Goat River suggested their migration to be best correlated to decreasing temperature and discharge. If the logistic model were representative of the population, then predicted migrations of burbot to the Goat River during winter would have followed a consistent pattern in November preLibby Dam, while postLibby Dam showed migrations to be unpredictable. Results of this study suggest that burbot had multiple life history patterns and several spawning locations and that rehabilitation measures should promote cooler winter water temperatures less than 5°C and discharges less than 300 m&lt;sup&gt;3&lt;/sup&gt;/s.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.191
Teacher spread0.182 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2008
Admission routes1
Has abstractyes

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