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Record W2946578083 · doi:10.24908/pocus.v2i1.13270

Case Report: A wolf in another wolf’s clothing: point-of-care ultrasound in a patient with an acute exacerbation of chronic obstructive pulmonary disease

2017· article· en· W2946578083 on OpenAlexvenueno aff
Jordan Leitch, Nicole Rocca

Bibliographic record

VenuePOCUS Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineExacerbationIntensive care unitIntensive care medicinePulmonary diseaseCritically illDiseaseMedical historyEmergency medicineMedical emergencySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Patients often present to hospital, and to the Intensive Care Unit (ICU) in particular, in situations that render them unable to provide an accurate (or any) clinical history to facilitate diagnosis. These patients also typically have multiple, serious medical co-morbidities, which further makes diagnosing and initiating an appropriate treatment difficult. Furthermore, the investigations performed to optimally diagnose acute critical medical conditions are often only possible in remote locations in the hospital or only available during regular daytime work hours, both of which are a concern with critically ill patients.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.025
GPT teacher head0.325
Teacher spread0.299 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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