P01.48. Biomechanical responses to the mechanical characteristics of a spinal manipulation: effect of varying segmental contact site
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".