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Record W4405072619 · doi:10.1183/13993003.01849-2024

Uncovering early COPD? The T-slope as a novel CT biomarker for evaluating airway narrowing

2024· letter· en· W4405072619 on OpenAlexaff
Miranda Kirby, Grace Párraga

Bibliographic record

VenueEuropean Respiratory Journal · 2024
Typeletter
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsWestern UniversityToronto Metropolitan University
Fundersnot available
KeywordsMedicineAirwayLumen (anatomy)COPDAirway obstructionLungComputed tomographyMucusRadiologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Extract From the tracheobronchial tree structure models described by Weibel [1], Horsfield and Cumming [2], and others [3, 4], we know that in the normal lung, the airways follow a branching pattern from the trachea to the distal airways, which locks in a progressive increase in cumulative cross-sectional lumen area. In fact, in the healthy lung, this increase in cross-sectional lumen area is exponential! The small airways, <2 mm in diameter, which can appear as early as the fourth generation of airway branches [5], are believed to be the major site of airflow obstruction in patients with COPD [6]. This insight was based on small airway disease features, including airway narrowing and obliteration, as well as mucus plugging. Using micro-computed tomography (CT) imaging [7], the cross-sectional lumen area of the terminal bronchioles was also shown to be reduced by 99.7% in COPD patients relative to controls. Substantial decreases in the total cross-sectional lumen area in the small airways will necessarily result in deviations from the expected exponential relationship.

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)0.002
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0120.011
Insufficient payload (model declined to judge)0.0030.005

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 head0.075
GPT teacher head0.350
Teacher spread0.275 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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