MétaCan
Menu
Back to cohort
Record W2076256276 · doi:10.1139/f01-179

Laboratory assessment of the role of a larval pheromone and natural stream odor in spawning stream localization by migratory sea lamprey (<i>Petromyzon marinus</i>)

2001· article· en· W2076256276 on OpenAlexvenueno aff
Lance A. Vrieze, Peter W. Sorensen

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersU.S. Geological SurveyU.S. Fish and Wildlife Service
KeywordsPetromyzonLampreyOdorSTREAMSLarvaPheromoneBiologyOlfactionEcologyZoologyFisheryNeuroscience

Abstract

fetched live from OpenAlex

This study used large laboratory mazes and natural stream waters to test the role of olfactory cues, including a pheromone released by larvae, in spawning stream localization by migratory sea lamprey (Petromyzon marinus). We found that migratory lamprey strongly prefer stream water over lake water and that this response is dependent upon a functional olfactory system. Responses persisted among migratory lamprey even after stream water was diluted a thousand times but were not seen among non-migratory lamprey. Experiments using waters from five streams demonstrated that a larval pheromone is a key determinant of stream attractiveness: water from streams with larval populations were consistently more attractive than those without, and adding larval odor to the latter reversed this relationship. Larval odor was attractive at low, realistic concentrations, especially when presented together with natural stream water, suggesting that streams contain other odors that synergize the actions of the pheromone. Some, but not all, of the activity of the larval pheromone could be explained by two bile acids released by larvae (petromyzonol sulfate and allocholic acid). Together, these results strongly suggest that migratory lamprey locate streams using a larval pheromone. This cue could be useful in lamprey control.

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 score0.215
Threshold uncertainty score0.998

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 head0.004
GPT teacher head0.193
Teacher spread0.188 · 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

Citations121
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicFish Ecology and Management StudiesFrench-language works237,207