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Record W2106893659 · doi:10.1177/183335830503400203

Asthma Terminology and Classification in Hospital Records

2005· article· en· W2106893659 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Information Management · 2005
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsVictoria Park
FundersAustralian Research CouncilUniversity of SydneyWorld Health Organization
KeywordsTerminologyAsthmaDocumentationMedicineCurrent Procedural TerminologyFamily medicineProject commissioningPublishingNursingComputer sciencePolitical scienceLinguistics

Abstract

fetched live from OpenAlex

Asthma is a national health priority area in Australia, and there is significant interest in capturing relevant detail about hospitalisations as a result of asthma. A public submission received by the National Centre for Classification in Health from a large teaching hospital in Victoria suggested that current classification terminology in ICD-10-AM did not adequately reflect the terms recorded in clinical inpatient records, and that patterns and severity of asthma better reflected current clinical terminology in Australian hospitals. The purpose of this study was to determine the validity of the public submission and inform future changes to ICD-10-AM. A representative sample of over 3000 asthma records across Australia and New Zealand were extracted, and the asthma terminology documented and codes assigned were recorded and analysed. The study concluded that there was little support for either pattern terminology or the current classification terminology; however, severity of asthma was commonly used in asthma documentation.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.300
Teacher spread0.283 · 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