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Record W4206988170 · doi:10.1123/jab.2021-0255

Characteristics of Forces at the Clinician–Patient and Patient–Table Interfaces During Thoracic Spinal Manipulation in Asymptomatic Adults Are Consistent With Deformable Body Models

2022· article· en· W4206988170 on OpenAlexaff
Joshua M. Thomas, Thomas J. Murphy, Steve Tran, Samuel J. Howarth, David Starmer, Martha Funabashi

Bibliographic record

VenueJournal of Applied Biomechanics · 2022
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversité du Québec à Trois-RivièresCanadian Memorial Chiropractic College
Fundersnot available
KeywordsInterface (matter)Table (database)AsymptomaticSimulationPhysical medicine and rehabilitationMedicineComputer sciencePhysical therapySurgeryData mining

Abstract

fetched live from OpenAlex

Investigating all forces exerted on the patient's body during high-velocity, low-amplitude spinal manipulative therapy (SMT) remains fundamental to elucidate how these may contribute to SMT's effects. Previous conflicting findings preclude our understanding of the relationship between SMT forces acting at the clinician-patient and patient-table interfaces. This study aimed to quantify forces at the clinician-participant and participant-table interfaces during thoracic SMT in asymptnomatic adults. An experienced clinician provided a posterior to anterior SMT centered to T7 transverse processes using predetermined force-time characteristics to 40 asymptomatic volunteers (20 females; average age = 27.2 [4.9] y). Forces at the clinician-participant interface were recorded by triaxial load cells; whereas, forces at the participant-table interface were recorded by the force-sensing table technology. Preload force, total peak force, time to peak, and loading rate at each interface were analyzed descriptively. Total peak vertical forces at the clinician-participant interface averaged 532 (71) N while total peak forces at the participant-table interface averaged 658 (33) N. Forces at the participant-table interface were, on average, 1.27 (0.25) times larger than the ones at the clinician-participant interface. Larger forces at the participant-table interface compared with the ones at the clinician-participant interface during thoracic SMT are consistent with mathematical models developed to investigate thoracic impact simulating a dynamic force-deflection response.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.267
Teacher spread0.248 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations13
Published2022
Admission routes1
Has abstractyes

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