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Social modulation of and by pain in humans and rodents

2015· article· en· W2061866699 on OpenAlexaff
Jeffrey S. Mogil

Bibliographic record

VenuePain · 2015
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiopsychosocial modelEmpathyNeurosciencePsychologyParallelsSocial neuroscienceCognitive psychologyCognitive sciencePsychotherapistSocial cognitionSocial psychologyCognition

Abstract

fetched live from OpenAlex

The social domain of the biopsychosocial model of pain has been greatly understudied compared with the biological and psychological domains but holds great promise for furthering our understanding, and better treatment, of pain. Recent years have seen an explosion of interest in social neuroscience and have revealed the ability of pain stimuli to alter social interactions. These experiments suggest that rodents are capable of producing simplified versions of any number of social phenomena involving empathy, previously thought to be the sole province of human beings. This review describes the state of science in both humans and nonhuman animals, and notes intriguing parallels in observations from both species. Indeed, my laboratory is starting to demonstrate perfectly translatable findings regarding social modulation of pain in rodents and humans.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.365
Teacher spread0.307 · 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

Citations126
Published2015
Admission routes1
Has abstractyes

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