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Record W1874004071 · doi:10.1109/cic.1990.144216

3D reconstruction of myocardial ischaemia from 16 site praecardial 24-hour ST mapping

2002· article· en· W1874004071 on OpenAlexaff
R.D. Seegobin, Rowland R. Tinline

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsQueen's University
Fundersnot available
KeywordsMyocardial ischemiaBlood pressureCardiologyHeart rateMyocardial ischaemiaMedicineInternal medicineChannel (broadcasting)Computer scienceIschemiaComputer network

Abstract

fetched live from OpenAlex

Summary form only given. The use of a three-dimensional CAD program. Autocad 10, to display the ST data in a 3D format is described. Each channel of ST data is converted to a polyline. The polylines representing ST change over time are structured as a grid to reproduce the physical positioning of the electrodes on the chest. In each of the four planes generated by the polylines of the grid, a mesh is layered over the polylines to correlate the ST change in each plane. A simultaneous mesh is generated of the change in heart rate. Such a modeling technique alloys a unique perspective of ischemic episodes in the 24 hours after anesthesia. Myocardial events can be correlated to other myocardial indices such as heart rate, systolic, diastolic and mean blood pressure, and pulmonary artery measurements if available. A 16-channel praecardial map may provide the potential for defining the area of ischaemia, and from this, the site of the comprised coronary arterial tree.>

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0260.002

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 head0.023
GPT teacher head0.227
Teacher spread0.204 · 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 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
Published2002
Admission routes1
Has abstractyes

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