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High-resolution CT phenotypes in pulmonary sarcoidosis: a multinational Delphi consensus study
Sujal R. Desai, Nishanth Sivarasan, Kerri A. Johannson, Peter M. George, Daniel A. Culver, Anand Devaraj, David A. Lynch, David Milne, Elisabetta Renzoni, Hilario Nunès, Nicola Sverzellati, Paolo Spagnolo, Robert P. Baughman, Ruchi Yadav, Sara Piciucchi, Simon Walsh, Vasileios Kouranos, Athol U. Wells, Adam Anderson, Adam S. Morgenthau, Adrián Gaser, А. A. Vizel, Alexandra Speranskaya, Alicia K. Gerke, Altinisik Goksel, Álvaro Undurraga, Amita Sharma, Andrea Oh, Ann N. Leung, Anna Rita Larici, Antje Prasse, Antonietta Mazzei, António Morais, Ashu Seith Bhalla, Belén del Río, Bhavin Jankharia, Brett M. Elicker, Carlos A.C. Pereira, Catherine Biegelman-Aubry, Charles S. White, Claudia Ravaglia, Connie C. W. Hsia, Cornelia Schaefer‐Prokop, David Launay, Deepak Talwar, Diego Castillo, Divya Patel, Dominique Israël‐Biet, Dominique Valeyre, E. James Britt, Elena Bargagli, Elisabeth Bendstrup, Elliott D. Crouser, Esther J. Nossent, Eugeny Shmelev, Eva Carmona Porquera, Francesco Bonella, Fleur Cohen‐Aubart, Florence Jeny, Giovanni Ferrara, Gong Yong Jin, Hasti Robbie, Helmut Prosch, Hiromitsu Sumikawa, Ho Ling-Pei, Ho Yun Lee, Irina Strâmbu, Ivette Buendía-Roldán, Jan Grutters, Jay H. Ryu, Jeff Swigris, Jelle Miedema, Jin Mo Goo, Joseph Barnett, Johny Verschakelen, Jonathan Goldin, Joon Beom Seo, Juan Ignacio Enghelmayer, Juan Mañá, Karen Patterson, Κατερίνα Αντωνίου, Kevin M. Brown, Kiminori Fujimoto, Laurent Savale, Lisa A. Maier, Luca Richeldi, Manuel L. Ribeiro Neto, Marc Humbert, Marc A. Judson, Marcel Veltkamp, Margaret Wilsher, María Molina‐Molina, María Otaola, Marie‐Pierre Revel, Mario Silva, Marjolein Drent, Mark L. Schiebler, Marlies Wijsenbeek-Lourens, Martina Bonifazi, Martine Rémy‐Jardin, Matthew Koslow, Meyer Balter, Michael Kreuter, Muhunthan Thillai, Nabeel Hamzeh, Nazia Chaudhuri, Nesrin Moğulkoç, Nevins W. Todd, Nick Screaton, Nicole Goh, Nirav G. Shah, Ogugua Ndili, Oksana A. Shlobin, Olga Baranova, Paul Bresser, Paula Rottoli, Pierre‐Yves Brillet, Qonita Said-Hartley, Raphaël Borie, Rémy L.M. Mostard, Richard N. van Zyl-Smit, Ronaldo Adib Kairalla, Ryoko Egashira, Samia Boussouar, Sang Min Lee, Sanjeev Bhalla, Sara Tomassetti, Sílvia Quadrelli, Simon P. Hart, Sonye K. Danoff, Sujeet Rajan, Sun Mi Choi, Susan J. Copley, Tae Jung Kim, Takeshi Johkoh, Tamera J. Corte, Theresa C. McLoud, Thomas Wessendorf, Tiago M. Alfaro, Toru Arai, Ulrich Costabel, Vanesa Vicens‐Zygmunt, Venerino Poletti, Vincent Cottin, Violeta Vučinić, Wim Wuyts, Wouter van Es, Yeon Joo Jeong, Yoshikazu Inoue
Bibliographic record
VenueThe Lancet Respiratory Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicSarcoidosis and Beryllium Toxicity Research
Canadian institutionsUniversity of Calgary
FundersNational Institute for Health and Care Research
KeywordsMedicineDelphi methodSarcoidosisDelphiMultinational corporationLikert scaleRadiologyMedical physicsPathologyPsychologyArtificial intelligence
Abstract
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 imitationNot 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.215
Threshold uncertainty score0.607
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.127
GPT teacher head0.381
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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
Citations67
Published2023
Admission routes1
Has abstractno