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Record W2132826329 · doi:10.1148/radiol.2015141579

CT-Definable Subtypes of Chronic Obstructive Pulmonary Disease: A Statement of the Fleischner Society

2015· article· en· W2132826329 on OpenAlexaff
David A. Lynch, John H. M. Austin, James C. Hogg, Philippe Greniér, Hans‐Ulrich Kauczor, Alexander A. Bankier, R. Graham Barr, Thomas V. Colby, Jeffrey R. Galvin, Pierre Alain Gevenois, Harvey O. Coxson, Eric A. Hoffman, John D. Newell, Massimo Pistolesi, Edwin K. Silverman, James D. Crapo

Bibliographic record

VenueRadiology · 2015
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Environmental Health SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood Institute
KeywordsMedicineCOPDBronchiectasisLungComputed tomographicAirwayAir trappingPulmonary diseaseRadiologyObstructive lung diseaseLung diseasePathologyRespiratory diseaseInternal medicineComputed tomographySurgery

Abstract

fetched live from OpenAlex

The purpose of this statement is to describe and define the phenotypic abnormalities that can be identified on visual and quantitative evaluation of computed tomographic (CT) images in subjects with chronic obstructive pulmonary disease (COPD), with the goal of contributing to a personalized approach to the treatment of patients with COPD. Quantitative CT is useful for identifying and sequentially evaluating the extent of emphysematous lung destruction, changes in airway walls, and expiratory air trapping. However, visual assessment of CT scans remains important to describe patterns of altered lung structure in COPD. The classification system proposed and illustrated in this article provides a structured approach to visual and quantitative assessment of COPD. Emphysema is classified as centrilobular (subclassified as trace, mild, moderate, confluent, and advanced destructive emphysema), panlobular, and paraseptal (subclassified as mild or substantial). Additional important visual features include airway wall thickening, inflammatory small airways disease, tracheal abnormalities, interstitial lung abnormalities, pulmonary arterial enlargement, and bronchiectasis.

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)0.027
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.025
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0020.006
Scholarly communication0.0030.004
Open science0.0030.004
Research integrity0.0080.013
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.291
Teacher spread0.268 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations641
Published2015
Admission routes1
Has abstractyes

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