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Record W2871400816 · doi:10.1038/s41591-018-0090-y

Reducing protein oxidation reverses lung fibrosis

2018· article· en· W2871400816 on OpenAlexaff
Vikas Anathy, Karolyn G. Lahue, David G. Chapman, Shi Biao Chia, Dylan T. Casey, Reem Aboushousha, Jos van der Velden, Evan A. Elko, Sidra M. Hoffman, David H. McMillan, Jane T. Jones, James D. Nolin, Sarah Abdalla, Robert H. Schneider, David J. Seward, Elle C. Roberson, Matthew D. Liptak, Morgan E. Cousins, Kelly J. Butnor, Douglas J. Taatjes, Ralph C. Budd, Charles G. Irvin, Ye‐Shih Ho, Razqallah Hakem, Kevin K. Brown, Reiko Matsui, Markus Bachschmid, José L. Gómez, Naftali Kaminski, Albert van der Vliet, Yvonne Janssen‐Heininger

Bibliographic record

VenueNature Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer Research
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Institute of General Medical SciencesNational Cancer InstituteNational Institute of Diabetes and Digestive and Kidney DiseasesNatureNational Heart, Lung, and Blood InstituteNational Institute on Aging
KeywordsBleomycinPulmonary fibrosisFibrosisLungIdiopathic pulmonary fibrosisMedicinePathologyInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.289
Teacher spread0.282 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations121
Published2018
Admission routes1
Has abstractno

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