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Record W4381850584 · doi:10.1016/j.jtho.2023.06.011

European Epidemiology of Pleural Mesothelioma—Real-Life Data From a Joint Analysis of the Mesoscape Database of the European Thoracic Oncology Platform and the European Society of Thoracic Surgery Mesothelioma Database

2023· article· en· W4381850584 on OpenAlexaff
Isabelle Opitz, Andrea Billè, Urania Dafni, Kristiaan Nackaerts, Luca Ampollini, Marc de Perrot, Luka Brčić, Ernest Nadal, Konstantinos Syrigos, Steven G. Gray, Joachim G.J.V. Aerts, Alessandra Curioni‐Fontecedro, Jan H. Rüschoff, Kim Monkhorst, Birgit Weynand, Enrico Maria Silini, Fatemeh Bavaghar-Zaeimi, Marko Jakopović, Roger Llatjós, Sotirios Tsimpoukis, Stephen P. Finn, Jan H. von der Thüsen, Nesa Marti, Georgia Dimopoulou, Roswitha Kammler, Solange Peters, Rolf A. Stahel, Pierre‐Emmanuel Falcoz, Alessandro Brunelli, Anita Hiltbrunner, Rosita Kammler, Barbara Ruepp, Zoi Tsourti, Panagiota Zygoura, Katerina Vervita, Charitini Andriakopoulou, Androniki Stavrou, Martina Haberecker, Susanne Dettwiler, Fabiola Prutek, Christiane Mittmann, Bart Vrugt, Martina Friess, Alessandra Matter, Chloé Spichiger-Häusermann, Michaela B. Kirschner, Emanuela Felley‐Bosco, Eric Verbeken, Philippe Nafteux, Johnny Moons, Liesbet M. Peeters, Marcello Tiseo, Letizia Gnetti, Paolo Carbognani, Miroslav Samaržija, Sven Seiwerth, Susana Lorente, Ioannis Vamvakaris, Paraskevi Boura, Mutaz Mohammed Nur, Anne‐Marie Baird, Sinéad Cuffe, Kathy Gately, Stefano Passani

Bibliographic record

VenueJournal of Thoracic Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersETOP IBCSG Partners FoundationSwiss Cancer Research FoundationSanofiAmgenPfizerGenentechInvitaeEli Lilly and Company
KeywordsMedicineMesotheliomaDatabaseHazard ratioEpidemiologyInternal medicineCohortMalignancyConfidence intervalCardiothoracic surgerySurgeryOncologyPathology

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)0.003
metaresearch head score (Gemma)0.011
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.006
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.124
GPT teacher head0.416
Teacher spread0.292 · 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

Citations16
Published2023
Admission routes1
Has abstractno

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