MétaCan
Menu
Back to cohort
Record W4311175873 · doi:10.4193/rhin22.344

The EUFOREA pocket guide for chronic rhinosinusitis

2022· article· en· W4311175873 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRhinology Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsUniversité de Montréal
FundersSanofi GenzymeRegeneron PharmaceuticalsSanofi
KeywordsMedicineRhinologyChronic rhinosinusitisNasal polypsSinusitisPosition paperAsthmaIntensive care medicinePopulationQuality of life (healthcare)OtorhinolaryngologyEnvironmental healthInternal medicinePathologySurgery

Abstract

fetched live from OpenAlex

Chronic rhinosinusitis (CRS) is known to affect around 5 % of the total population, with major impact on the quality of life of those severely affected (1). Despite a substantial burden on individuals, society and health economies, CRS often remains underdiagnosed, under-estimated and under-treated (2). International guidelines like the European Position Paper on Rhinosinusitis and Nasal Polyps (EPOS) (3) and the International Consensus statement on Allergy and Rhinology: Rhinosinusitis 2021 (ICAR) (4) offer physicians insight into the recommended treatment options for CRS, with an overview of effective strategies and guidance of diagnosis and care throughout the disease journey of CRS.

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.

Full frame distilled prediction

Teacher imitation

Not 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.300
Teacher spread0.283 · 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