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The allergen bronchoprovocation model: an important tool for the investigation of new asthma anti‐inflammatory therapies

2007· review· en· W2003417718 on OpenAlexaff
L.‐P. Boulet, G.M. Gauvreau, Marie‐Ève Boulay, Paul M. O’Byrne, Don Cockcroft

Bibliographic record

VenueAllergy · 2007
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversity of SaskatchewanMcMaster University Medical CentreUniversité LavalRoyal University Hospital
Fundersnot available
KeywordsMedicineAsthmaAllergenImmunologyAllergy

Abstract

fetched live from OpenAlex

Allergen bronchoprovocation tests have been used for more than two decades in the investigation of respiratory allergic diseases such as asthma and rhinitis. These bronchial challenges are now well standardized and can offer key information on the therapeutic potential of new agents and on their anti-inflammatory effects on the airways. Both standard and low-dose allergen provocations are safe when performed by experienced investigators and do not lead to persistent worsening of asthma or change in airway function. The evaluation of new therapeutic agents by these methods can also provide important information on the mechanisms of development and persistence of airway diseases.

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)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.004

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 head0.057
GPT teacher head0.341
Teacher spread0.284 · 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
GenreReview

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

Citations74
Published2007
Admission routes1
Has abstractyes

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