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Record W2494791456 · doi:10.1007/978-1-62703-517-0_11

Converging Methodologies in a Mammalian “Simple System” Focused on the Biology of Memory: Conditioned Odor Preference in the Neonate Rat

2013· book-chapter· en· W2494791456 on OpenAlexaff
Qi Yuan, Carolyn W. Harley, John H. McLean

Bibliographic record

VenueNeuromethods · 2013
Typebook-chapter
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsOdorOlfactory bulbPreferenceNeuroscienceBiologyCognitive scienceComputer sciencePsychologyCognitive psychologyCentral nervous system

Abstract

fetched live from OpenAlex

We present here a critical period model for odor preference learning in the rat pup, which can produce short-term or lifelong changes in odor-related behaviors depending on training parameters. Features which make it a powerful tool for the analysis of memory processes are described. The chapter outlines four behavioral protocols and then provides an overview of a range of methodologies, primarily physiological, which we have used to probe the circuit changes produced by training. Each of these approaches offers different strengths for an experimental dissection of how the olfactory bulb, or any neural structure, is changed by learning. The direction they provide both supports and modifies popular hypotheses in the biology of memory.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.467
GPT teacher head0.352
Teacher spread0.115 · 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 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

Citations2
Published2013
Admission routes1
Has abstractyes

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