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Record W1984641358 · doi:10.1103/physrevlett.84.4773

Stochastic Resonance Enhances the Electrosensory Information Available to Paddlefish for Prey Capture

2000· article· en· W1984641358 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

VenuePhysical Review Letters · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
Topicstochastic dynamics and bifurcation
Canadian institutionsUniversity of British ColumbiaCanadian Institute for Advanced Research
Fundersnot available
KeywordsDaphniaStochastic resonancePredationRostrumSIGNAL (programming language)Computer scienceBiological systemBiologyPhysicsFisheryStatistical physicsZooplanktonNoise (video)EcologyArtificial intelligenceImage (mathematics)

Abstract

fetched live from OpenAlex

Recent behavior experiments have demonstrated that paddlefish can make use of stochastic resonance while feeding on Daphnia plankton. Here we calculate the information content of the noisy Daphnia signal at the paddlefish rostrum using an exact statistical treatment of threshold stochastic resonance as a minimal neural model. These calculations compare well with experimentally obtained data on paddlefish strikes at Daphnia prey.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.516
Threshold uncertainty score0.624

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 studies0.0000.000
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 head0.008
GPT teacher head0.247
Teacher spread0.240 · 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