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Record W2990545681 · doi:10.11124/jbisrir-d-19-00080

Center of rotation locations during lumbar spine movements

2019· article· en· W2990545681 on OpenAlexaff
Martha Funabashi, Alexander Breen, Diana De Carvalho, Alison Henry, Kent Murnaghan, Isabelle Pagé, Arnold Yu Lok Wong, Gregory N. Kawchuk

Bibliographic record

VenueThe JBI Database of Systematic Reviews and Implementation Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsUniversity of AlbertaMemorial University of NewfoundlandCanadian Memorial Chiropractic College
Fundersnot available
KeywordsLumbar spineRotation (mathematics)LumbarCenter (category theory)MedicineGeodesyPhysical medicine and rehabilitationAnatomyGeologyComputer scienceArtificial intelligenceSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this review is to identify and map current literature describing the center of rotation locations and migration paths during lumbar spine movements. INTRODUCTION: Altered lumber spine kinematics has been associated with pain and injury. Intervertebral segments' center of rotations, the point around which spinal segments rotate, are important for determining the features of lumbar spine kinematics and the potential for increased injury risk during movements. Although many studies have investigated the center of rotations of humans' lumbar spine, no review has summarized and organized the state of the science related to center of rotation locations and migration paths of the lumbar spine during lumbar spine movements. INCLUSION CRITERIA: This review will consider studies that include human lumbar spines of any age and condition (e.g. heathy, pathological) during lumbar spine movements. Quantitative study designs, including clinical, observational, laboratory biomechanical experimental studies, mathematical and computer modeling studies will be considered. Only studies published in English will be included, and there will be no limit on dates of publication. METHODS: PubMed, MEDLINE, Embase, the Cochrane Library Controlled Register of Trials, CINAHL, ACM Digital Library, Compendex, Inspec, Web of Science, Scopus, Google Scholar, and dissertation and theses repositories will be searched. After title and abstract screening of identified references, two independent reviewers will screen the full-text of identified studies and extract data. Data will be summarized and categorized, and a comprehensive narrative summary will be presented with the respective results.

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)0.004
metaresearch head score (Gemma)0.025
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: Review
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0100.008
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.041
GPT teacher head0.369
Teacher spread0.328 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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