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Record W1981151186 · doi:10.1186/1472-6882-12-s1-p48

P01.48. Biomechanical responses to the mechanical characteristics of a spinal manipulation: effect of varying segmental contact site

2012· article· en· W1981151186 on OpenAlexaff
Tiffany L. Edgecombe, Gregory N. Kawchuk, Cynthia R. Long, Joel G. Pickar

Bibliographic record

VenueBMC Complementary and Alternative Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineStiffnessLow back painManual therapyPhysical medicine and rehabilitationPhysical therapySpinal manipulationMetric (unit)Alternative medicinePathologyStructural engineeringEngineering

Abstract

fetched live from OpenAlex

In an anesthetized cat preparation (n=8), simulated SMT was delivered by a validated mechanical apparatus to the intact lumbar spine at 4 sites: L 6 spinous process, left L 6 lamina, left L 6 mammillary process, and L 7 spinous process. To obtain stiffness data, the apparatus slowly displaced the L 6 spinous process to 16N; force and displacement were recorded continuously. Three metrics were calculated from the resulting force-displacement curve: Terminal Instantaneous Stiffness (TIS, stiffness at the end point of the curve), k (average stiffness), and Regional Stiffness (RS, average stiffness in each 10% interval of the curve). SMT-induced changes in each metric were determined for each application site using an ANOVA model controlling for SMT presentation order. SMT applied at the L 6 spinous decreased TIS (-0.48N/mm [-0.86, -0.09] upper, lower 95%CI). SMT applied at the L 6 lamina also decreased TIS (-0.44N/mm; [-0.82, -0.05]). SMT applied to the L 6 spinous increased k (0.44N/mm, [-0.01, 088]). SMT applied at L 6 spinous process and L 6 lamina decreased RS during some, but not all intervals. These results suggest that previous reports on SMT’s effect on spinal stiffness may be influenced by the choice of SMT application site and stiffness metric.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.051
GPT teacher head0.361
Teacher spread0.310 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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