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Record W7065725801

Does Spinal Manipulative Therapy Impact the Immune System? A Rapid Review of the Literature

2020· other· en· W7065725801 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2020
Typeother
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsManual therapyRehabilitationImmune systemHealth careBiomedicineHealth professionals
DOInot available

Abstract

fetched live from OpenAlex

This is a protocol for a rapid review of the literature, using WHO Rapid Review Methods, to investigate the the impact of spinal manipulation on the immune system. Principal investigator: Pierre Côté, Faculty of Health Sciences and Centre for Disability Prevention and Rehabilitation at Ontario Tech University and CMCC, Ontario Tech University, Faculty of Health Sciences, 2000 Simcoe St N, Oshawa, ON L1G 0C5 Review team members: Pierre Côté, Carol Cancelliere, Silvano Mior, Ngai Chow, Anne Taylor-Vaisey, Stephen Injeyan, Julita Teodorczyk-Injeyan, J. David Cassidy

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)0.100
metaresearch head score (Gemma)0.219
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.100
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1000.219
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0230.011
Science and technology studies0.0030.003
Scholarly communication0.0090.008
Open science0.0040.006
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0360.013

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 head0.013
GPT teacher head0.274
Teacher spread0.261 · 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 designSystematic review
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

Citations0
Published2020
Admission routes1
Has abstractyes

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