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Record W2895096887 · doi:10.1097/rti.0000000000000365

Are We Overdiagnosing Pulmonary Embolism? Yes!

2018· review· en· W2895096887 on OpenAlex
Stéphanie Tan, Linda B. Haramati

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Thoracic Imaging · 2018
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsOverdiagnosisMedicinePulmonary embolismPulmonary angiographyRadiologyIntensive care medicineComputed tomographyComputed tomography angiographyCardiology

Abstract

fetched live from OpenAlex

Pulmonary embolism (PE) is a relatively common and potentially fatal pathology. Fear of missing the diagnosis is pervasive for physicians, including radiologists. However, as computed tomography pulmonary angiography technology and utilization have evolved over the years, we have gained an understanding that not all PEs are equal. As such, our interpretations of PE imaging studies must be enriched by this understanding and adapted to patient circumstances. Herein, we shine the light on overdiagnosis of PE, exploring the evidence, impact, costs, and consequences of overdiagnosis on the care of our patients.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.072
GPT teacher head0.416
Teacher spread0.344 · 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