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Record W2966481099 · doi:10.1016/j.jaip.2019.05.013

The Hidden Story of Nonadherence with Asthma Therapy: For a Few Dollars More?

2019· letter· en· W2966481099 on OpenAlexafffund
Job F. M. van Boven, Kenneth R. Chapman

Bibliographic record

VenueThe Journal of Allergy and Clinical Immunology In Practice · 2019
Typeletter
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchGenentechGrifolsAstraZenecaCSL BehringSanofiRocheRegeneron PharmaceuticalsNovartisUniversity Health NetworkBaxter InternationalGlaxoSmithKlineAmgenBoehringer Ingelheim
KeywordsMedicineAsthmaSurpriseIntensive care medicineMedication adherenceEndotypeDiseaseEmergency medicineFamily medicinePediatricsInternal medicine

Abstract

fetched live from OpenAlex

The World Health Organization (WHO) has estimated that as many as half of all patients prescribed medications for chronic disease are not taking their medication as prescribed.1 In one country alone, such nonadherence may contribute to approximately 125,000 preventable deaths and up to $289 billion of excess costs.2 Given asthma's symptom variability, its error-prone delivery systems, and reliance on patient self-monitoring, it should not surprise us that inhaled asthma drugs are among the medications with the lowest rates of nonadherence.

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)0.046
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.047
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0050.007
Open science0.0010.002
Research integrity0.0470.058
Insufficient payload (model declined to judge)0.0090.004

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 head0.028
GPT teacher head0.350
Teacher spread0.323 · 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
GenreCommentary

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".

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Citations2
Published2019
Admission routes2
Has abstractno

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