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Record W2117589985 · doi:10.4187/respcare.08531283

Wheeze Detection in the Pediatric Intensive Care Unit

2008· editorial· en· W2117589985 on OpenAlexaff
Hans Pasterkamp

Bibliographic record

VenueRespiratory Care · 2008
Typeeditorial
Languageen
FieldMedicine
TopicPhonocardiography and Auscultation Techniques
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of ManitobaManitoba Health
Fundersnot available
KeywordsMedicineWheezeAsthmaRespiratory soundsPediatricsAirway obstructionPediatric intensive care unitAllergyAirwayIntensive careIntensive care medicineInternal medicineImmunologyAnesthesia

Abstract

fetched live from OpenAlex

If one excludes cough from the acoustic signs related to respiratory disease, wheezing becomes the most common adventitious lung sound. The whistling tones of wheezing are understood to originate from airway wall flutter when flow becomes limited during airway obstruction. 1 It is well recognized that “not all that wheezes is asthma,” but wheezing is most typically heard in patients with asthma. Questionnaires in epidemiologic surveys of asthma prevalence and severity (eg, the International Study of Asthma and Allergies in Childhood) 2 depend on inquiries about recent and past wheezing episodes. Young children with acute obstructive airway diseases are often characterized as “wheezy infants.” Phenotypes of wheezing in early life have been described, 3 but the diagnosis of asthma based on recurrent wheezing remains difficult in the individual young child.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.184
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.302
Teacher spread0.281 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2008
Admission routes1
Has abstractyes

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