MétaCan
Menu
Back to cohort
Record W2004226477 · doi:10.1139/z08-112

Pacific lamprey climbing behavior

2008· article· en· W2004226477 on OpenAlexvenueno aff
Ulrich G. Reinhardt, Laura Eidietis, Sarah E. Friedl, Mary L. Moser

Bibliographic record

VenueCanadian Journal of Zoology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersGreat Lakes Fishery Commission
KeywordsClimbingLampreyFish locomotionLampetraBiologyGeologyFisheryFish <Actinopterygii>Ecology

Abstract

fetched live from OpenAlex

New lamprey-friendly fishways feature inclined ramps that facilitate passage of Pacific lampreys ( Lampetra tridentata (Richardson, 1836)) over Bonneville Dam on the Columbia River, USA. We observed the lampreys moving against water at two flow volumes and on two ramps of 45° and 18° angles relative to horizontal. We documented climbing movements using high-speed video (125 frames/s). Lampreys advanced on the ramps by repeated cycles of attaching to the ramps by their sucker mouths (resting phase), bending their bodies into a W shape (stage II), and then, rapidly straightening the body to propel themselves up the ramp, with simultaneous brief (20–140 ms) release of suction (stage III). We inferred that lampreys were using burst swimming to propel themselves up the ramp, because we observed inflection points in the body curvature traveling toward the posterior of the body and the center of mass moving up, during stage III. This climbing behavior is not described for any other fish species. Vertical motion, relative to the ground, during each cycle of movement was greatest in the 45° ramp – low water flow volume treatment (mean of 0.07 L/cycle), but the movement upstream along the ramp plane was greatest on the 18° ramp, regardless of flow volume. These findings can be used to develop ramp designs that maximize lamprey climbing performance.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.198
Teacher spread0.183 · 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 source (direct Gemma or distilled Codex), 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

Citations41
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of ZoologySame topicFish Ecology and Management StudiesFrench-language works237,207