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Record W2556483487 · doi:10.1002/jnr.23831

Sex differences in neuroimmunity and pain

2016· review· en· W2556483487 on OpenAlexaff
Sarah F. Rosen, Boram Ham, Jeffrey S. Mogil

Bibliographic record

VenueJournal of Neuroscience Research · 2016
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsImmune modulationChronic painImmune systemPsychologyHormoneMedicineSex characteristicsGonadal hormonesNeuroscienceInternal medicineImmunologyCastration

Abstract

fetched live from OpenAlex

Differences in the prevalence of chronic pain in women vs. men are well known, and decades of laboratory experimentation have demonstrated that women are more sensitive to pain than are men. Attention has thus shifted to investigating mechanisms underlying such differences. Recent evidence suggests that neuroimmune modulation of pain may represent an important cause of sex differences. The current Review examines the evidence for gonadal hormone modulation of the immune system, immune system modulation of pain, and interactions that might help to explain sex differences in pain. © 2016 Wiley Periodicals, Inc.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.412
GPT teacher head0.511
Teacher spread0.099 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations321
Published2016
Admission routes1
Has abstractyes

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