MétaCan
Menu
Back to cohort
Record W2753340894 · doi:10.7717/peerj.3748

Preferences for achromatic horizontal, vertical, and square patterns in zebrafish ( <i>Danio rerio</i> )

2017· article· en· W2753340894 on OpenAlexafffund
Lisa Rimstad, Adam Holcombe, Alicia Pope, Trevor J. Hamilton, Melike Schalomon

Bibliographic record

VenuePeerJ · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsMacEwan UniversityWomen and Children’s Health Research InstituteUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaMacEwan University
KeywordsZebrafishDanioAchromatic lensPreferenceHorizontal and verticalBiologyFish <Actinopterygii>MathematicsOpticsFisheryPhysicsGeometryStatisticsGenetics

Abstract

fetched live from OpenAlex

) is gaining popularity as a laboratory organism and is used to model many human diseases. Many behavioural measures of locomotion and cognition have been developed that involve the processing of visual stimuli. However, the innate preference for vertical and horizontal stripes in zebrafish is unknown. We tested the preference of adult zebrafish for three achromatic patterns (vertical stripes, horizontal stripes, and squares) at three different size conditions (1, 5, and 10 mm). Each animal was tested once in a rectangular arena, which had a different pattern of the same size condition on the walls of either half of the arena. We show that zebrafish have differential preferences for patterned stimuli at each of the three size conditions. These results suggest that zebrafish have naïve preferences that should be carefully considered when testing zebrafish in paradigms using visual stimuli.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.025
GPT teacher head0.321
Teacher spread0.296 · 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

Citations6
Published2017
Admission routes2
Has abstractyes

Explore more

Same venuePeerJSame topicZebrafish Biomedical Research ApplicationsFrench-language works237,207