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Record W3105619653 · doi:10.7861/clinmed.2020-0661

Lessons of the month: A breathless severe asthmatic in the genomic era: Occam's razor or Hickam's dictum?

2020· article· en· W3105619653 on OpenAlexafffund
Carmen Venegas, Sarah Svenningsen, Melanie Kjarsgaard, Mark A. Tarnopolsky, Kim Anderson, Sebastian Levesque, Benjamin A. Raby, Grace Párraga, Gerard Cox, Parameswaran Nair

Bibliographic record

VenueClinical Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsWestern UniversityDalhousie UniversityMcMaster UniversityUniversité de SherbrookeSt. Joseph’s Healthcare Hamilton
FundersCanadian Institutes of Health ResearchPontificia Universidad Católica de ChileReseau canadien de recherche respiratoireTeva Pharmaceutical Industries
KeywordsMedicineBronchial thermoplastyGenetic testingMyopathyAsthmaIntensive care medicineCardiomyopathyPathologyCardiologyInternal medicineHeart failure

Abstract

fetched live from OpenAlex

Breathlessness is a subjective symptom that may stem from a number of pathological and functional aetiologies. Consequently, clinicians are often faced with the challenge of navigating between the tensions of Occam's razor (parsimonious aetiology) or Hickam's dictum (multiple diagnoses). We report a case of a 36-year-old woman with a lifelong history of episodic breathlessness caused at various times by dysfunctions of lung parenchyma (emphysema) and airway smooth muscle (asthma), skeletal muscle (filamin-C fibrillary myopathy) and cardiac muscle (cardiomyopathy). We illustrate the utility of the modern diagnostic toolbox in the assessment, understanding and management of complex dyspnoea (including the use of inflammometry, inhaled-gas magnetic resonance imaging-guided bronchial thermoplasty, and genetic testing), and also demonstrate the importance of interdisciplinary data interpretation in establishing accurate aetiologic diagnoses.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.099
GPT teacher head0.390
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2020
Admission routes2
Has abstractyes

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