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Increased luminal area of large conducting airways in patients with COVID-19 and post-acute sequelae of COVID-19: a retrospective case-control study

2024· article· en· W4402625713 on OpenAlexafffund
Solomiia Zaremba, Alex J. Miller, Erik A. Ovrom, Jonathon W. Senefeld, Chad C. Wiggins, Paolo B. Dominelli, Ravindra Ganesh, Ryan T. Hurt, Brian J. Bartholmai, Brian T. Welch, Juan G. Ripoll, Michael J. Joyner, Andrew H. Ramsook

Bibliographic record

VenueJournal of Applied Physiology · 2024
Typearticle
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsUniversity of Waterloo
FundersNational Heart, Lung, and Blood InstituteNatural Sciences and Engineering Research Council of Canada
KeywordsMedicineAirwayCoronavirus disease 2019 (COVID-19)BronchusSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Respiratory systemInternal medicineGastroenterologyRespiratory diseaseSurgeryLungDisease

Abstract

fetched live from OpenAlex

Three-dimensional reconstruction of airways has shown increased luminal area in patients with COVID-19 and post-acute sequelae of COVID-19 when compared with healthy controls. These findings suggest the role of large conducting airways in the pathogenesis of post-acute sequelae of COVID 19.

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)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.291
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

Citations1
Published2024
Admission routes2
Has abstractyes

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