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Record W2316614042 · doi:10.17849/0743-6661-45.3.153

Highly Sensitive Troponin and Critical Illness Insurance: Have the Goalposts Moved Again?

2015· article· en· W2316614042 on OpenAlexaff
A Senn, Timothy J. Meagher

Bibliographic record

VenueJournal of Insurance Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsTroponinMyocardial infarctionMedicineCardiologyInternal medicineSine qua nonTroponin ITroponin TIntensive care medicineLaw

Abstract

fetched live from OpenAlex

An elevated cardiac troponin is a sine qua non for the clinical diagnosis of myocardial infarction. The sensitivity of troponin assays has improved repeatedly since troponin entered clinical use in the late 1990s. Its most recent iteration, "highly sensitive" troponin will shortly enter clinical use in North America. It is able to detect amounts of troponin 10 times smaller than the current assay. As a result, more myocardial infarctions will be diagnosed. This may have an impact on the number of critical illness claims for heart attack.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.024
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0030.011
Scholarly communication0.0070.025
Open science0.0020.004
Research integrity0.0170.031
Insufficient payload (model declined to judge)0.0240.004

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 head0.033
GPT teacher head0.346
Teacher spread0.313 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreCommentary

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
Published2015
Admission routes1
Has abstractyes

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