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Record W2001971075 · doi:10.1159/000236269

Fenoterol and Death from Asthma in New Zealand

2009· article· en· W2001971075 on OpenAlexaboutno aff
Richard Beasley, Neil Pearce, John A. Crane, C. Burgess

Bibliographic record

VenueInternational Archives of Allergy and Immunology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPharmacological Effects and Assays
Canadian institutionsnot available
Fundersnot available
KeywordsFenoterolSalbutamolAsthmaMedicineEpidemiologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

This article reviews the epidemiological evidence that the use of fenoterol leads to an increased risk of death compared with other commonly used β-agonist drugs such as salbutamol, and that fenoterol was a causative factor in the second epidemic of asthma deaths in New Zealand. One of the features of this evidence is the consistency of the findings. In addition to evidence from three case-control studies in New Zealand and a recent study in Canada, the fenoterol hypothesis is also consistent with data on time trends in mortality and drugs sales, and with a large body of experimental evidence that fenoterol has relatively greater cardiac side effects, and that these may be hazardous in the situation of hypoxia.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.510

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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