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Record W3200909377 · doi:10.5114/ada.2021.103305

Nonsteroidal anti-inflammatory drugs exacerbated respiratory disease – the role of aspirin desensitisation in patients with nasal polyposis

2021· article· en· W3200909377 on OpenAlexaboutno aff
Dorota Jenerowicz, Joanna Szyfter-Harris, Dorota Miętkiewska-Leszniewska, Magdalena Czarnecka‐Operacz, Małgorzata Wierzbicka, Zygmunt Adamski, Witold Szyfter, Małgorzata Leszczyńska

Bibliographic record

VenueAdvances in Dermatology and Allergology · 2021
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAspirinNonsteroidalDermatologyGastroenterologyInternal medicine

Abstract

fetched live from OpenAlex

ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Jenerowicz D, Szyfter-Harris J, Miętkiewska-Leszniewska D, et al. Nonsteroidal anti-inflammatory drugs exacerbated respiratory disease – the role of aspirin desensitisation in patients with nasal polyposis. Postępy Dermatologii i Alergologii/Advances in Dermatology and Allergology. 2021. doi:10.5114/ada.2021.103305. APA Jenerowicz, D., Szyfter-Harris, J., Miętkiewska-Leszniewska, D., Czarnecka-Operacz, M., Wierzbicka, M., & Adamski, Z. et al. (2021). Nonsteroidal anti-inflammatory drugs exacerbated respiratory disease – the role of aspirin desensitisation in patients with nasal polyposis. Postępy Dermatologii i Alergologii/Advances in Dermatology and Allergology. https://doi.org/10.5114/ada.2021.103305 Chicago Jenerowicz, Dorota, Joanna Szyfter-Harris, Dorota Miętkiewska-Leszniewska, Magdalena Czarnecka-Operacz, Małgorzata Wierzbicka, Zygmunt Adamski, and Witold Szyfter et al. 2021. "Nonsteroidal anti-inflammatory drugs exacerbated respiratory disease – the role of aspirin desensitisation in patients with nasal polyposis". Postępy Dermatologii i Alergologii/Advances in Dermatology and Allergology. doi:10.5114/ada.2021.103305. Harvard Jenerowicz, D., Szyfter-Harris, J., Miętkiewska-Leszniewska, D., Czarnecka-Operacz, M., Wierzbicka, M., Adamski, Z., Szyfter, W., and Leszczyńska, M. (2021). Nonsteroidal anti-inflammatory drugs exacerbated respiratory disease – the role of aspirin desensitisation in patients with nasal polyposis. Postępy Dermatologii i Alergologii/Advances in Dermatology and Allergology. https://doi.org/10.5114/ada.2021.103305 MLA Jenerowicz, Dorota et al. "Nonsteroidal anti-inflammatory drugs exacerbated respiratory disease – the role of aspirin desensitisation in patients with nasal polyposis." Postępy Dermatologii i Alergologii/Advances in Dermatology and Allergology, 2021. doi:10.5114/ada.2021.103305. Vancouver Jenerowicz D, Szyfter-Harris J, Miętkiewska-Leszniewska D, Czarnecka-Operacz M, Wierzbicka M, Adamski Z et al. Nonsteroidal anti-inflammatory drugs exacerbated respiratory disease – the role of aspirin desensitisation in patients with nasal polyposis. Postępy Dermatologii i Alergologii/Advances in Dermatology and Allergology. 2021. doi:10.5114/ada.2021.103305.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.004
GPT teacher head0.227
Teacher spread0.223 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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