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Record W2768668936 · doi:10.1183/23120541.00067-2017

<i>Aspergillus fumigatus</i>-specific immunoglobulin levels in BALF of CF patients

2017· article· en· W2768668936 on OpenAlexaff
Mia Goña-Höpler, Birgit Pfaller, Jonathan Argeny, Stefan Kanolzer, Saskia Gruber, Klara Schmidthaler, Sabine Renner, Edith Nachbaur, P. Fucik, Andreas Glaser, Markus Debiasi, Zsolt Szépfalusi, Reto Crameri, Claudio Rhyner, Thomas Eiwegger

Bibliographic record

VenueERJ Open Research · 2017
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersOesterreichische NationalbankSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsAspergillus fumigatusMedicineCystic fibrosisImmunoglobulin EMicrobiologyAspergillusAntibodyImmunologyAspergillosisImmunoglobulin GAllergic bronchopulmonary aspergillosisInternal medicineBiology

Abstract

fetched live from OpenAlex

A lack of correlation between systemic and local IgE production at mucosal sites has been reported for allergic asthma [1–5], allergic rhinitis [6, 7] and chronic rhinosinusitis with nasal polyps [8–10]. In allergic asthmatics, local IgE production is higher than in nonallergic asthmatics [3] and high local IgE levels have been linked to the clinical phenotype. Interestingly, in cases of nasal polyps, local IgE targets mainly superantigens [8]. IgE responses to Aspergillus fumigatus in cystic fibrosis lungs <http://ow.ly/XXwv30furqs> T. Eiwegger was involved in the conception, hypotheses delineation and design of the study. E. Nachbaur, Z. Szépfalusi, T. Eiwegger, J. Argeny, S. Kanolzer, K. Schmidthaler, P. Fucik, M. Goña-Höpler, R. Crameri, A.G. Glaser, C. Rhyner and M. Debiasi were involved in acquisition, analysis and interpretation of the data. M. Goña-Höpler and B. Pfaller were involved in analysis and writing the article. S. Renner, E. Nachbaur, Z. Szépfalusi and T. Eiwegger were involved in critical review of the manuscript.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.003
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 head0.204
GPT teacher head0.483
Teacher spread0.279 · 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 teacher head, not a consensus.

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

Citations1
Published2017
Admission routes1
Has abstractyes

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