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Record W6907817920 · doi:10.25384/sage.c.4181855.v1

Feasibility of an Audit System for Canadian Sonographers in Generalist Ultrasound

2018· other· en· W6907817920 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSonographerAuditUltrasoundDiagnostic ultrasoundMeasure (data warehouse)

Abstract

fetched live from OpenAlex

The purpose of this research was to employ the audit method to measure performance and identify targets of change, setting a template for future large-scale investigations that may inform decisions involving sonographer role expansion in Canada. The authors conducted an audit of 433 sonographic examinations performed in the ultrasound department of a Canadian hospital. Sonographer reports were contrasted with radiologist final reports, and a degree of agreement (DoA) 1 to 4 was assigned to each exam package. In total, 322 of 429 (75%) exam packages were ranked as DoA 1 (complete agreement between sonographer and radiologist), 86 of 429 (20%) were ranked as DoA 2, 16 of 429 (4%) were ranked as DoA 3, and 5 of 429 (1%) were ranked as DoA 4 (significant discrepancy between sonographer and radiologist). The results revealed a 75% agreement between sonographer and radiologist on imaging findings as they are recorded in technical impression sheets and reports. Discrepancies are usually minor and involve the omission of incidental findings by the radiologist.

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)0.090
metaresearch head score (Gemma)0.162
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.653

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0900.162
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0050.001
Scholarly communication0.0040.003
Open science0.0030.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.097
GPT teacher head0.350
Teacher spread0.253 · 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.

Study designObservational
DomainEvaluation
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

Citations0
Published2018
Admission routes1
Has abstractyes

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