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Record W2082558554 · doi:10.1089/zeb.2011.0720

Behavioral Measure of Frequency Detection and Discrimination in the Zebrafish, <i>Danio rerio</i>

2012· article· en· W2082558554 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZebrafish · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of WindsorUniversity of Ottawa
Fundersnot available
KeywordsDanioZebrafishAudiogramAudiologyBiologyFish <Actinopterygii>ReinforcementPsychologyHearing lossMedicineFishery

Abstract

fetched live from OpenAlex

Behavioral tests of hearing in fish are relatively rare and are generally based upon aversive conditioning, with little data available for the positive reinforcement methods common in other vertebrates. Despite its increasing importance as an auditory model, no behavioral hearing measures have been conducted on zebrafish (Danio rerio), with only physiological hearing estimates available. In the current study, a new behavioral testing paradigm is developed to assess sound detection abilities of zebrafish and the effect of training frequency on hearing sensitivity. Zebrafish were trained to respond to either a 400 Hz or a 1000 Hz tone, and behavioral thresholds were then measured to tones from 200 to 1000 Hz. Significant threshold differences existed between the behavioral audiograms, with fish from each set most sensitive to their conditioned frequency. Furthermore, fish acoustically conditioned to 1000 Hz were most sensitive to the upper range of test frequencies (600-1000 Hz). This appears to be the first study utilizing a positive reinforcement behavioral assay for testing hearing in zebrafish and provides further evidence of fine-scale auditory filtering in fish.

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.

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)0.001
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 score0.070
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.246
Teacher spread0.221 · 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