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Record W2328092028 · doi:10.1097/rct.0b013e3181ef9fbe

Repeated Low-Dose Computed Tomography in Current and Former Smokers for Quantification of Emphysema

2010· article· en· W2328092028 on OpenAlex

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 Computer Assisted Tomography · 2010
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineComputed tomographyCurrent (fluid)Nuclear medicineTomographyPulmonary emphysemaRadiologyInternal medicineLung

Abstract

fetched live from OpenAlex

OBJECTIVE: To quantify different emphysema evolution in current and former smokers. METHODS: We retrospectively analyzed low-dose computed tomography scans from a lung cancer screening study of 59 current and 75 former smokers. The quantitative emphysema analysis was performed using a home-built software (YACTA version 0.9), yielding the parameters lung volume, emphysema volume (EV), emphysema index (EI), mean lung density, and 15th percentile. RESULTS: The baseline EV and EI were significantly different (median EVformer =422 mL vs EVcurrent =249 mL, P = 0.0003; and median EIformer =7.6 % vs EIcurrent =4.1 %, P = 0.0001, respectively). On the annual repeat scan, the median EI and EV for former smokers had decreased significantly (ΔEIformer = -0.257%, P = 0.004; and ΔEVcurrent = -0.203 mL, P = 0.020), whereas there was no emphysema change in current smokers. CONCLUSIONS: We were able to demonstrate different emphysema evolution in current versus former smokers; emphysema parameters decreased in the former smokers and remained stable in current smokers.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
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 head0.022
GPT teacher head0.313
Teacher spread0.290 · 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