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Record W1898300100

Death duties: workshop on what family physicians are expected to do when patients die.

2007· article· en· W1898300100 on OpenAlexaffabout
Kathryn Myers, Eden David

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldMedicine
TopicAutopsy Techniques and Outcomes
Canadian institutionsSt Joseph's Health Care
Fundersnot available
KeywordsCoronerCertificationCertificateMedicineDeath certificateTest (biology)Cause of deathFamily medicineMedical educationMedical emergencyComputer sciencePoison controlSuicide preventionLawPathology
DOInot available

Abstract

fetched live from OpenAlex

PROBLEM BEING ADDRESSED: Family physicians are often called upon to pronounce and certify the deaths of patients. Inadequate knowledge of the Coroners Act (in the province of Ontario) and of the correct process of certifying death can make physicians uncomfortable when confronted with these tasks. OBJECTIVE OF PROGRAM: To educate family physicians about how to perform the administrative tasks required of them when patients die. PROGRAM DESCRIPTION: The program included an educational video, a tutorial outlining the process of death certification, and discussion with a regional coroner about key features of the Coroners Act. In small groups, participants worked through cases of patient deaths in which they were asked to determine whether a coroner needed to be involved, to determine the manner of death, and to complete a mock death certificate for each case. CONCLUSION: All participants reported a high level of satisfaction with the workshop and thought the main objective of the program had been achieved. Results of a test given 3 months after the workshop showed substantial improvement in participants' knowledge of the coroner's role and of the process of death certification.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.688

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 head0.031
GPT teacher head0.272
Teacher spread0.241 · 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

Citations8
Published2007
Admission routes2
Has abstractyes

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