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Assessing the recommendations for the use of diagnostic imaging in clinical practice guidelines

2012· article· en· W1509438354 on OpenAlexaff
Martin H. Reed

Bibliographic record

VenueJournal of Evidence-Based Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of ManitobaManitoba Health
Fundersnot available
KeywordsClinical PracticeAppropriate Use CriteriaMedicineMedical physicsMedical imagingDiagnostic accuracyDiagnostic testEvidence-based medicineQuality of evidenceEvidence-based practiceRadiologyAlternative medicinePediatricsPhysical therapyRandomized controlled trialPathologyInternal medicine

Abstract

fetched live from OpenAlex

Accuracy is the primary evidence assessed when diagnostic imaging is evaluated in clinical practice guidelines. However, recommendations to not use diagnostic imaging are usually based not on its accuracy but on its lack of utility, that is its low Level 4 efficacy. If there is good clinical evidence that diagnostic imaging will not be useful in a clinical situation, the recommendation not to use it should be strong even if the evidence for its accuracy is of poor quality.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Evaluation · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptMetaresearch
Domain: Evaluation · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.012
metaresearch head score (Gemma)0.335
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.335
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.658
GPT teacher head0.588
Teacher spread0.070 · 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

Labeled directly by 2 models reading the full record.

Study designSystematic review
DomainEvaluation
GenreReview

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

Citations2
Published2012
Admission routes1
Has abstractyes

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