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Record W2072904453 · doi:10.1037/0097-7403.31.2.125

Multiple Systems for Spatial Learning: Dead Reckoning and Beacon Homing in Rats.

2005· article· en· W2072904453 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

VenueJournal of Experimental Psychology Animal Behavior Processes · 2005
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHoming (biology)Dead reckoningPsychologyArtificial intelligenceComputer scienceBiologyTelecommunicationsGlobal Positioning SystemEcology

Abstract

fetched live from OpenAlex

Rats homed with food in a large lighted arena. Without visual cues, they used dead reckoning. When a beacon indicated the home, rats could also use the beacon. Homing did not differ in 2 groups of rats, 1 provided with the beacon and 1 without it; tests without the beacon gave no evidence that beacon learning overshadowed dead reckoning (Experiment 1). When the beacon was at the home for 1 group and in random locations for another, there was again no evidence of cue competition (Experiment 2). Dead reckoning experience did not block acquisition of beacon homing (Experiment 3). Beacon learning and dead reckoning do not compete for predictive value but acquire information in parallel and are used hierarchically.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.656

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 head0.127
GPT teacher head0.407
Teacher spread0.281 · 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