MétaCan
Menu
Back to cohort
Record W4200071447 · doi:10.1038/s41586-021-04177-9

Combinatorial, additive and dose-dependent drug–microbiome associations

2021· article· en· W4200071447 on OpenAlexaff
Sofia K. Forslund, Rima Chakaroun, Maria Zimmermann‐Kogadeeva, Lajos Markó, Judith Aron‐Wisnewsky, Trine Nielsen, Lucas Moitinho‐Silva, Thomas Schmidt, Gwen Falony, Sara Vieira‐Silva, Solia Adriouch, Renato Alves, Karen E. Assmann, Jean‐Philippe Bastard, Till Birkner, Robert Caesar, Julien Chilloux, Luís Pedro Coelho, Léopold Fezeu, Nathalie Galleron, Gérard Helft, Richard Isnard, Boyang Ji, Michael Kuhn, Emmanuelle Le Chatelier, Antonis Myridakis, Lisa Olsson, Nicolas Pons, Edi Prifti, Benoît Quinquis, Hugo Roume, Joe‐Elie Salem, Nataliya Sokolovska, Valentina Tremaroli, Mireia Valles‐Colomer, Christian Lewinter, Nadja B. Søndertoft, Helle Pedersen, Tue H. Hansen, Chloé Amouyal, Ehm Astrid Andersson Galijatovic, Fabrizio Andreelli, Olivier Barthelemy, Jean-Paul Batisse, Eugeni Belda, Magali Berland, Randa Bittar, Hervé Blottière, F Bosquet, Rachid Boubrit, Olivier Bourron, Mickael Camus, Dominique Cassuto, Cécile Ciangura, Jean‐Philippe Collet, Maria-Carlota Dao, Morad Djebbar, Angélique Doré, Line Engelbrechtsen, Soraya Fellahi, Sébastien Fromentin, Pilar Galán, Dominique Gauguier, Philippe Giral, Agnès Hartemann, Bolette Hartmann, Jens J. Holst, Malene Hornbak, Lesley Hoyles, Jean‐Sébastien Hulot, Sophie Jaqueminet, Niklas Rye Jørgensen, Hanna Julienne, Johanne Marie Justesen, Judith Kammer, Nikolaj T. Krarup, Mathieu Kernéis, Jean Khémis, Ruby Kozlowski, Véronique Lejard, Florence Levenez, Lea Lucas-Martini, Robin Massey, Laura Martínez-Gili, Nicolas Maziers, Jonathan Medina-Stamminger, Gilles Montalescot, Sandrine Moute, Ana Luísa Neves, Michael Olanipekun, Laetitia Pasero Le Pavin, Christine Poitou, Françoise Pousset, Laurence Pouzoulet, Andrea Rodriguez‐Martinez, Christine Rouault, Johanne Silvain, Mathilde Svendstrup, T.D. Swartz, Thierry Vanduyvenboden, Camille Vatier, Stefanie Walther, Jens Peter Gøtze, Lars Køber, Henrik Vestergaard, Torben Hansen, Jean‐Daniel Zucker, Serge Herçberg, Jean‐Michel Oppert, Ivica Letunić, Jens Nielsen, Fredrik Bäckhed, S. Dusko Ehrlich, Marc‐Emmanuel Dumas, Jeroen Raes, Oluf Pedersen, Karine Clément, Michael Stümvoll, Peer Bork

Bibliographic record

VenueNature · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcGill University and Génome Québec Innovation Centre
FundersH2020 European Research CouncilInstitut de Cardiométabolisme et NutritionNIHR Imperial Biomedical Research CentreConseil Régional Hauts-de-FranceAssistance publique-Hôpitaux de ParisHorizon 2020 Framework ProgrammeNovo Nordisk FondenMedical Research CouncilNovo Nordisk Foundation Center for Basic Metabolic ResearchJulius-Maximilians-Universität WürzburgInstitut National de la Santé et de la Recherche MédicaleEli Lilly and CompanyLundbeckfondenYonsei UniversitySanofiDanoneEuropean CommissionHelmholtz Zentrum MünchenNovo NordiskNational Institute for Health and Care ResearchCHIST-ERAAgence Nationale de la RechercheAstraZenecaDeutsche Forschungsgemeinschaft
KeywordsMicrobiomeDrugComputational biologyBiologyPharmacologyGenetics

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)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.004
GPT teacher head0.258
Teacher spread0.254 · 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

Citations237
Published2021
Admission routes1
Has abstractno

Explore more

Same venueNatureSame topicGut microbiota and healthFrench-language works237,207