The carbon footprint of diagnostic delays in asthma
Bibliographic record
Abstract
Asthma is a prevalent chronic disease worldwide [1], yet its diagnosis remains a challenge [2]. The difficulty partly stems from bronchial provocation testing (BPT) diagnostic delays, a highly sensitive yet specialised procedure [3–6]. Footnotes This manuscript has recently been accepted for publication in the ERJ Open Research . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJOR online. Please open or download the PDF to view this article. Conflict of interest: LP, LD, SEL, SLP, and MD declare no conflicts of interest. Conflict of interest: CCP: reports speaker honoraria from AstraZeneca, GlaxoSmithKline, and Sanofi-Regeneron; he received consultancy fees from AstraZeneca, GlaxoSmithKline, and Sanofi-Regeneron. Conflict of interest: SL reports speaker honoraria from AstraZeneca outside of the submitted work. Conflict of interest: FAV reports speaker honoraria from AstraZeneca, Sanofi-Regeneron, GlaxoSmithKline, Boehringer Ingelheim and Novartis outside of the submitted work. Conflict of interest: PL reports speaker honoraria from AstraZeneca, Sanofi-Regeneron, GlaxoSmithKline, Boehringer Ingelheim and Novartis outside of the submitted work: he received consultancy fees from AstraZeneca, GlaxoSmithKline, and Sanofi-Regeneron. Conflict of interest: SC reports the following: he has received non-restricted research grants from the NIHR Oxford BRC, the Quebec Respiratory Health Research Network, the Fondation Québécoise en Santé Respiratoire, the Academy of Medical Sciences, AstraZeneca, bioMérieux, and Sanofi-Genyme-Regeneron; he is the holder of the Association Pulmonaire du Québec's Research Chair in Respiratory medicine and is a Clinical research scholar of the Fonds de recherche du Québec; he received speaker honoraria from AstraZeneca, GlaxoSmithKline, Sanofi-Regeneron, and Valeo Pharma; he received consultancy fees for FirstThought, AstraZeneca, GlaxoSmithKline, Sanofi-Regeneron, Access Biotechnology and Access Industries; he has received sponsorship to attend/speak at international scientific meetings by/for AstraZeneca and Sanofi-Regeneron. He is an advisory board member and will have stock options for Biometry Inc – a company which is developing a FeNO device (myBiometry). He advised the Institut national d'excellence en santé et services sociaux (INESSS) for an update of the asthma general practice information booklet for general practitioners.
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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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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.
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.
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".