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Record W3074476114 · doi:10.31885/jrn.1.2020.1318

Have we reproduced Rat Park? Conceptual but not direct replication of the protective effects of social and environmental enrichment in addiction

2020· article· en· W3074476114 on OpenAlexaff
Shaun Yon‐Seng Khoo

Bibliographic record

VenueJournal for Reproducibility in Neuroscience · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAddictionEnvironmental enrichmentReplication (statistics)PsychologyConsumption (sociology)Substance abuseBiologyPsychiatryNeuroscienceSociologySocial science

Abstract

fetched live from OpenAlex

The Rat Park studies are classic experiments in addiction neuroscience, yet they have not been successfully replicated directly and several serious methodological criticisms have been raised. However, the conceptual reproducibility of the Rat Park studies is supported by both contemporaneous and subsequent research. Contemporaneous research on social and environmental enrichment frequently found social isolation rendered rats less sensitive to the effects of drugs of abuse. The Rat Park studies therefore confirmed the importance of social and environmental enrichment and extended this literature to suggest that enrichment reduced opioid consumption. Subsequent studies have also demonstrated social and environmental enrichment reduces drug consumption. However, there are also several papers reporting no effects of enrichment (or ‘negative’ results) and caveats from studies that show genes, age, sex and drug of abuse are all important parameters. While the Rat Park studies did not use methods that are reliable by current standards, enrichment has been shown to reliably reduce opioid consumption and this effect can generalise to other drugs of abuse.

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)0.042
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.074
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.009
Scholarly communication0.0020.005
Open science0.0030.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.060
GPT teacher head0.313
Teacher spread0.253 · 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.

Study designBench or experimental
DomainReproducibility
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
Published2020
Admission routes1
Has abstractyes

Explore more

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