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Record W2737538269 · doi:10.15326/jcopdf.4.3.2016.0180

Serum Proteins Associated with Emphysema Progression in Severe Alpha-1 Antitrypsin Deficiency

2017· article· en· W2737538269 on OpenAlexaff
Tatsiana Beiko, Michael G. Janech, Alexander V. Alekseyenko, Carl Atkinson, Harvey O. Coxson, Jeremy L. Barth, Sarah Stephenson, Carole L. Wilson, Lynn M. Schnapp, Alan R. Barker, Mark Brantly, Robert A. Sandhaus, Edwin K. Silverman, James K. Stoller, Bruce C. Trapnell, Charlie Strange

Bibliographic record

VenueChronic Obstructive Pulmonary Diseases Journal of the COPD Foundation · 2017
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of British Columbia
FundersNational Center for Research ResourcesNational Institute of General Medical SciencesMedical Research CouncilNational Institutes of HealthCHEST FoundationAlpha-1 Foundation
KeywordsAlpha 1-antitrypsin deficiencyMedicineBiomarkerAlpha (finance)Pulmonary emphysemaDiseasePathologyLungInternal medicineBiologySurgeryGenetics

Abstract

fetched live from OpenAlex

panel) in 31 individuals with a complete dataset. We analyzed associations between initial PD15/TLC, PD15/TLC annual decline, body mass index (BMI), and protein levels using Pearson's product moment correlation. C-reactive protein (CRP), adipocyte fatty acid-binding protein (AFBP), leptin, and tissue plasminogen activator (tPA) were found to be associated with baseline emphysema and all but leptin were associated with emphysema progression after adjustments were made for age and sex. All 4 proteins were associated with BMI after further adjustment for multiple comparisons was made. The relationship between these proteins and BMI, and further validation of these findings in replicative cohorts require additional studies.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.303
Teacher spread0.287 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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