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Record W2321871277 · doi:10.1097/jom.0000000000000286

Advanced Diagnostic Studies

2014· review· en· W2321871277 on OpenAlexaffabout
Catherine Lemière

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2014
Typereview
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsExhaled nitric oxideSputumMedicineOccupational asthmaEosinophilAsthmaInhalationInternal medicineEosinophil cationic proteinImmunologyIntensive care medicinePathologySpirometryAnesthesiaTuberculosis

Abstract

fetched live from OpenAlex

AIM: : The present paper aims to review the advantages and limitations of sputum cell counts and exhaled nitric oxide (FeNO) levels in the investigation of occupational asthma (OA). METHODS: The American College of Chest physicians held a course on occupational and Environmental Lung Diseases in Toronto in 2013. A summary of the session on non-invasive measures of airway inflammation in OA is presented here. RESULTS: Occupational asthma is associated with an increase in sputum eosinophil percentage during periods at work or after positive specific inhalation challenges. Changes in FeNO are less sensitive than sputum eosinophil counts for predicting OA. CONCLUSIONS: In settings where this tool is available, sputum eosinophil counts may complement the current investigation of OA. The interpretation of FeNO remains sometimes difficult. The phenotypes of patients who may benefit from this measure needs to be better defined.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.032
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0320.018

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 head0.067
GPT teacher head0.399
Teacher spread0.332 · 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 designSystematic review
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

Citations4
Published2014
Admission routes2
Has abstractyes

Explore more

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