MétaCan
Menu
Back to cohort

Update on the Nasal Polyp Score

2025· preprint· W4415381984 on OpenAlexaff
Philippe Gevaert, Elke Vandewalle, Isam Alobid, Claus Bachert, Adam Chaker, Cemal Cingi, Eugenio De Corso, Joaquim Mullol, Jianlong Han, Peter W. Hellings, Valérie Hox, William C. Torres J., Ludger Klimek, Stella E. Lee, Valerie Lund, Ralph Mösges, Oliver Pfaar, Sietze Reitsma, G. K, Thibaut Van Zele, Stephan Vlaminck, Martin Wagenmann, Sanna Toppila‐Salmi, Claire Hopkins

Bibliographic record

Venuenot available
Typepreprint
Language
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsNasal polypsChronic rhinosinusitisNoseAllergyMEDLINERhinology

Abstract

fetched live from OpenAlex

To the EditorIn 2022, a group of clinician scientists working in the field of research in chronic rhinosinusitis with nasal polyps (CRSwNP), came together under the auspices of the European Academy of Allergy and Clinical Immunology (EAACI) to achieve

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.005
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0050.002
Science and technology studies0.0000.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.007

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 head0.048
GPT teacher head0.294
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same topicNasal Surgery and Airway StudiesFrench-language works237,207