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Record W6959414643 · doi:10.11575/prism/27898

Stroke in Railway Workers, Pilots and Commercial Vehicle Operators: The Risk of a Future Event

2016· other· en· W6959414643 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2016
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsEvent (particle physics)Consistency (knowledge bases)Risk assessmentRisk factorWork (physics)Stroke (engine)Narrative reviewOccupational safety and health

Abstract

fetched live from OpenAlex

Medical guidelines, for individuals who have had a cerebrovascular event and who work in occupations where critical attention is required, lack consistency between occupations and across different areas of the world. Airline pilots, railway engineers and commercial vehicle operators are examples of individuals who cross international boarders frequently and need guidelines for safe return to work after an initial stroke. These individuals are at risk of a second catastrophic event including death, a myocardial infarction, syncope, seizures, or recurrent ischemic or hemorrhagic stroke. Medical guidelines should include occupational risk level, diagnosis of the initial event, assessment of the patient by medical evaluation and testing, risk factor evaluation and suggestions for further testing. A risk threshold to determine if an individual will go on to have a second event, stratified by diagnosis and other risk factors, should be stated in these guidelines. However, the risk that an individual in the working age group will go on to have a second event is not well understood. The first paper of this thesis is a narrative overview of the current medical guidelines in place for air, rail and road transport in Canada, the USA, the UK and Australia. The second paper is a systematic review and meta analysis looking at the risk that an individual with a first ever cerebrovascular event in the working age group will go on to have a catastrophic event.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.394
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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