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Record W4205207589 · doi:10.1183/23120541.00570-2021

Predicting the benefits of type-2 targeted anti-inflammatory treatment with the prototype Oxford Asthma Attack Risk Scale (ORACLE)

2022· article· en· W4205207589 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

VenueERJ Open Research · 2022
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversité de Sherbrooke
FundersUniversity of OxfordNational Institute for Health and Care ResearchWellcome TrustWellcome
KeywordsMedicineAsthmaOracleInflammationScale (ratio)Internal medicineOncologyImmunologyProgramming language

Abstract

fetched live from OpenAlex

Reduction of the risk of severe asthma attacks is a major goal of current guidelines [1]. The observation that blood eosinophils and exhaled nitric oxide fraction ( F ENO) identify the higher risk type-2 inflammatory phenotype in asthma is potentially relevant to this goal [2]. The prototype ORACLE scale based on two simple measures of type 2 airway inflammation (blood eosinophils and F ENO) quantifies the excess risk conferred by raised biomarkers that is removed by type-2 anti-inflammatory treatment in trial populations <https://bit.ly/3F1gnUl> The authors acknowledge colleagues and patients in the Oxford University Hospitals Foundation Trust's severe asthma clinic for inspiration, help and proofreading.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.062
GPT teacher head0.361
Teacher spread0.300 · 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