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Record W2159048442 · doi:10.1002/dev.20139

Artificial rearing alters the response of rats to natural and drug-mediated rewards

2006· article· en· W2159048442 on OpenAlexaff
Anna M. Lomanowska, Shadna A. Rana, D. McCutcheon, Linda A. Parker, P.E. Wainwright

Bibliographic record

VenueDevelopmental Psychobiology · 2006
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsWilfrid Laurier UniversityUniversity of Waterloo
Fundersnot available
KeywordsOpen fieldPsychologyEmotionalityElevated plus mazeDevelopmental psychologyAnxietyPreferencePhysiologyInternal medicineEndocrinologyMedicine

Abstract

fetched live from OpenAlex

Artificial rearing (AR) of infant rats permits precise control over key features of the early environment without maternal influence. The present study examined the behavioral response of AR rats towards natural and drug-mediated rewards, as well as their exploratory and affective behaviors. Adolescent AR rats showed increased preference for sucrose consumption relative to chow and demonstrated greater activity in the open field and in the elevated plus-maze compared to maternally reared (MR) rats. With respect to measures of emotionality, AR rats showed enhanced avoidance of the open arms of the plus-maze, indicating increased anxiety, but they did not differ from MR rats in exploring the center of the open field. Adult AR rats displayed a stronger conditioned response to morphine in a place preference test. These findings support the potential of the AR model to contribute to understanding the role of early experience in the development of behavioral motivation.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.315
Teacher spread0.294 · 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 designObservational
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

Citations30
Published2006
Admission routes1
Has abstractyes

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