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Record W2070297012 · doi:10.1016/s0161-4754(02)54130-0

Calibration and electrical safety status of therapeutic ultrasound used by chiropractic physicians

2003· article· en· W2070297012 on OpenAlexaboutno aff
Dwain M Daniel, Ronald L. Rupert

Bibliographic record

VenueJournal of Manipulative and Physiological Therapeutics · 2003
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsChiropracticMedicineUltrasoundCalibrationPatient safetyTherapeutic ultrasoundMedical physicsPhysical therapyMedical emergencyAlternative medicineRadiologyHealth careStatisticsPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Ultrasound therapy is a commonly used therapeutic modality within the chiropractic profession. Previous calibration studies of ultrasound units within the physical therapy communities in Scotland and Canada have shown that approximately two thirds of units tested did not conform to minimum calibration standards. Similar failure rates may exist in the chiropractic profession and need to be addressed. OBJECTIVE: To determine whether ultrasound machines used by chiropractic physicians met established calibration and electrical safety standards, and to assess frequency of ultrasound therapy use. DESIGN: This cross-sectional study tested 45 ultrasound units for ultrasonic output and electrical safety. Additionally, we asked the doctors to complete a short survey relating to education, usage, and maintenance of their ultrasound equipment. RESULTS: Of the 45 machines tested, 44% failed either calibration or electrical safety inspection. Failure rate was age dependent (P < or =.05). Only 2 of the 45 machines tested had been safety checked within the last year. CONCLUSIONS: A large percentage of ultrasound machines in chiropractic physicians' offices deliver too much or too little dosage to the patient. Electrical safety inspections also revealed a significant failure rate. Chiropractic physicians must become more aware of the requirement for yearly calibration and safety inspections, and understand that failure to maintain their equipment could result in loss of therapeutic effectiveness and pose a threat to the safety of their patients and staff.

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)0.003
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.056
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.249
GPT teacher head0.393
Teacher spread0.144 · 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 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

Citations17
Published2003
Admission routes1
Has abstractyes

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