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Record W3048439205 · doi:10.1183/13993003.02108-2020

COVID-19 and COPD

2020· editorial· en· W3048439205 on OpenAlexafffund
Janice M. Leung, Masahiro Niikura, Cheng Wei Tony Yang, Don D. Sin

Bibliographic record

VenueEuropean Respiratory Journal · 2020
Typeeditorial
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BCProvidence Health CareAstraZeneca
KeywordsMedicineCOPDCoronavirus disease 2019 (COVID-19)PneumoniaSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakLungLung infectionInternal medicineIntensive care medicineImmunologyVirologyDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

COPD patients have increased risk of severe pneumonia and poor outcomes when they develop COVID-19. This may be related to poor underlying lung reserves or increased expression of ACE-2 receptor in small airways.https://bit.ly/37dSB8l

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)0.005
metaresearch head score (Gemma)0.015
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: Editorial
Teacher disagreement score0.016
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.001
Science and technology studies0.0030.002
Scholarly communication0.0050.005
Open science0.0030.002
Research integrity0.0160.024
Insufficient payload (model declined to judge)0.0150.015

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 head0.038
GPT teacher head0.334
Teacher spread0.296 · 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

Citations304
Published2020
Admission routes2
Has abstractyes

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