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Record W4415931265 · doi:10.1038/s41591-025-04091-x

Publisher Correction: Academia Europaea’s guidelines for the visualization of clinical outcomes

2025· article· en· W4415931265 on OpenAlexaff
Péter Hegyi, András Garami, Àlvar Agustí, Charles Agyemang, Arturo Anadón, József Balla, Maciej Banach, Derrick Bennett, Traolach Brugha, Jan K. Buitelaar, Félix Carvalho, J. M. Castro Cerón, Adam Cohen, Turgay Dalkara, Ann K. Daly, Peter Dayan, Wouter W. de Herder, Stefano Del Prato, Dobromir Dobrev, Maria Dorobanţu, Margaret M. Esiri, Bart C.J.M. Fauser, Péter Ferdinandy, Rebecca C. Fitzgerald, Roberto Gambari, Arnold Ganser, Helen Giamarellou, Vivette Glover, Andrzej Grzybowski, Balázs Gulyás, Pancras C.W. Hogendoorn, Peter Holzer, Hilleke E. Hulshoff Pol, Mihajlo Jakovljević, Heikki Joensuu, Gábor Juhász, Jaakko Kaprio, Éva Kondorosi, Georg Langs, Chak Sing Lau, Jeffrey Laurence, Francesca Levi‐Schaffer, Ronan A Lyons, Aiping Lü, M. N. V. Ravi Kumar, Giuseppe Mancia, Brendan McCormack, Iain McInnes, Hugh McKenna, Françis Mégraud, M. Misrahi, Godefridus J. Peters, Ole H. Petersen, Vincent Piguet, Thierry Poynard, Ling Qin, Željko Reiner, Pieter H. Reitsma, Gerhard Rogler, Martin N. Rossor, Catherine Sackley, Philippa T. K. Saunders, Rainer Schulz, Matthias Schwab, Walter Sermeus, Shahrokh F. Shariat, Niels E. Skakkebæk, Ewout W. Steyerberg, Michael Swash, Zoltán Szekanecz, Jean Paul Thiery, David R. Thompson, András Varró, Michael Vieth, Michel Wensing, Hasan Yazıcı, Jun Yu, Mone Zaidi, Alimuddin Zumla, Viktória Barna, Marie Anne Engh, Richárd Farkas, Andrea Harnos, Rita Nagy, Mahmoud Obeidat, Anett Rancz, Brigitta Teutsch, Gábor Varga, Szilárd Váncsa, Alexander Schulze Wenning, Annapoorna Kuppuswamy, Kinga Morsanyi, Katalin Solymosi

Bibliographic record

VenueNature Medicine · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsWomen's College HospitalUniversity of TorontoUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsVisualizationMEDLINEData visualizationInformation visualization

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)0.036
metaresearch head score (Gemma)0.468
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.964
Threshold uncertainty score0.526

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.468
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0140.015
Science and technology studies0.0030.005
Scholarly communication0.0130.005
Open science0.0080.005
Research integrity0.0130.017
Insufficient payload (model declined to judge)0.1570.080

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 head0.820
GPT teacher head0.694
Teacher spread0.126 · 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.

Study designNot applicable
DomainReporting
GenreMethods

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
Published2025
Admission routes1
Has abstractno

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