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Record W4210773546 · doi:10.1038/s41591-021-01655-5

Intestinal Akkermansia muciniphila predicts clinical response to PD-1 blockade in patients with advanced non-small-cell lung cancer

2022· article· en· W4210773546 on OpenAlexafffund
Lisa Derosa, Bertrand Routy, Andrew Maltez Thomas, Valerio Iebba, Gérard Zalcman, S. Friard, Julien Mazières, Clarisse Audigier-Valette, Denis Moro‐Sibilot, François Goldwasser, Carolina Alves Costa Silva, Safae Terrisse, Mélodie Bonvalet, Arnaud Scherpereel, Hervé Pegliasco, Corentin Richard, François Ghiringhelli, Arielle Elkrief, Antoine Desîlets, Félix Blanc‐Durand, Fabio Cumbo, Aitor Blanco‐Míguez, Romain Boidot, Sandy Chevrier, Romain Daillère, Guido Kroemer, Laurie Alla, Nicolas Pons, Emmanuelle Le Chatelier, Nathalie Galleron, Hugo Roume, Agathe Dubuisson, Nicole Bouchard, Meriem Messaoudene, Damien Drubay, Éric Deutsch, Fabrice Barlési, David Planchard, Nicola Segata, Stéphanie Martinez, Laurence Zitvogel, Jean‐Charles Soria, Benjamin Besse

Bibliographic record

VenueNature Medicine · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health ResearchLabex Immuno-OncologyNational Institutes of HealthDa VolterraDaiichi Sankyo EuropeNational Cancer InstituteServierFondation Gustave RoussyDirection Générale de l’offre de SoinsChancellerie des Universités de ParisInstitut Universitaire de FranceLigue Contre le CancerMinistero dell’Istruzione, dell’Università e della RicercaHorizon 2020 Framework ProgrammeFondation pour la Recherche MédicaleInstitut National de la Santé et de la Recherche MédicaleInstitute of Cancer ResearchInstitut Du Cancer de MontréalAgence Nationale de la RechercheFondation LeducqFondation ARC pour la Recherche sur le CancerE-RareInstitut National Du CancerAstraZenecaNovocureTaiho PharmaceuticalCelgeneGenentechInstitut Gustave-RoussyCancer Prevention and Research Institute of TexasEuropean CommissionSanofiGlaxoSmithKlineSeerave FoundationAssociation pour la Recherche sur le CancerRelay TherapeuticsAmgenSymphogenPfizerEli Lilly and CompanySamsungBristol-Myers Squibb
KeywordsAkkermansia muciniphilaAkkermansiaBiologyInternal medicineOncologyGut floraGastroenterologyCancer researchImmunologyMedicineBacteriaBacteroidesGenetics

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 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)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.005
GPT teacher head0.303
Teacher spread0.298 · 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

Citations642
Published2022
Admission routes2
Has abstractno

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