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Enhanced Recognition of “Lung Sliding” with Power Color Doppler Imaging in the Diagnosis of Pneumothorax

2002· article· en· W2060304069 on OpenAlexaff
Johann Cunningham, Andrew W. Kirkpatrick, Savvas Nicolaou, David Liu, Douglas R. Hamilton, Bernard Lawless, Mark Lee, D. Ross Brown, Richard K. Simons

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2002
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsVancouver Hospital and Health Sciences CentreVancouver General Hospital
Fundersnot available
KeywordsPower dopplerPneumothoraxMedicineArtArt historyPhilosophySurgeryUltrasonography

Abstract

fetched live from OpenAlex

Cunningham, Johann MD, FRCSC; Kirkpatrick, Andrew W. MD, FRCSC; Nicolaou, Savvas MD, FRCPC; Liu, David MD; Hamilton, Douglas R. MD; Lawless, Bernard MD, FRCSC; Lee, Mark BSc, CDR; Brown, D. Ross MD, FRCSC; Simons, Richard K. MD, FRCSC Author Information

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)0.001
metaresearch head score (Gemma)0.012
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0020.001
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 head0.035
GPT teacher head0.345
Teacher spread0.310 · 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

Citations99
Published2002
Admission routes1
Has abstractyes

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