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Record W2885989508 · doi:10.1002/jmri.26202

Hyperpolarized <sup>3</sup>He MRI ventilatory apparent diffusion coefficient of alpha‐1 antitrypsin deficiency

2018· letter· fr· W2885989508 on OpenAlexafffund
Andrew Westcott, Dante P. I. Capaldi, Alexei Ouriadov, David G. McCormack, Grace Párraga

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2018
Typeletter
Languagefr
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsRobarts Clinical TrialsWestern University
FundersCanadian Institutes of Health Research
KeywordsUniversity hospitalMedicineLibrary scienceClassicsHistoryFamily medicineComputer science

Abstract

fetched live from OpenAlex

Alpha-1 antitrypsin deficiency (AATD) leads to disabling chronic obstructive pulmonary disease (COPD). Current therapy aimed at slowing lung disease progression includes exogenous alpha-1 antitrypsin augmentation therapy, but there are few potential new treatments under development. Currently used measurements of AATD-related emphysema include the forced expiratory volume in 1 second (FEV1) and the diffusing capacity of carbon monoxide (DLCO); both are relatively insensitive to therapy, although computed tomography (CT) lung density measurements have been shown to worsen more slowly in treated patients.

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)0.000
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0040.003
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 head0.012
GPT teacher head0.257
Teacher spread0.246 · 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
Published2018
Admission routes2
Has abstractno

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