Manipulation Peak Forces Across Spinal Regions for Children Using Mannequin Simulators
Bibliographic record
Abstract
OBJECTIVE: The purpose of this work was to create an exploratory database of manipulation treatment force variability as a function of the intent of an experienced clinician sub-specializing in the care of children to match treatment to childhood category. Data of this type are necessary for realistic planning of dose-response and safety studies on therapeutic benefit. METHODS: The project evaluated the transmitted peak forces of procedures applied to mannequins of different stature for younger and older children. Common procedures for the cervical, thoracic, and lumbar spine and sacroiliac joint were administered to estimate variability by a single experienced practitioner and educator in pediatric manipulation attempting to modulate for childhood category. Results described for peak components in the cardinal axes and for peak total forces were cataloged and compared with consensus estimates of force from the literature. RESULTS: Mean force values for both components and total force peaks monotonically increased with childhood category analogous to consensus expectations. However, a mismatch was observed between peak values measured and consensus predictions that ranged by a factor of 2 to 3.5, particularly in the upper categories. Quantitative data permit a first estimate of effect size for future clinical studies. CONCLUSIONS: The findings of this study indicate that recalibration of spinal manipulation performance of experienced clinicians toward arbitrary target values similar to consensus estimates is feasible. What is unclear from the literature or these results is the identity of legitimate target values that are both safe and clinically effective based on childhood categories in actual practice.
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 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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".