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Record W3111140533 · doi:10.1016/j.xjon.2020.11.013

Commentary: Mobilizing the reserves in coronary artery bypass grafting with and without fractional flow

2020· editorial· en· W3111140533 on OpenAlexaboutno aff
Torsten Doenst, Mahmoud Diab, Gloria Faerber, Markus Richter

Bibliographic record

VenueJTCVS Open · 2020
Typeeditorial
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsFractional flow reserveConventional PCIMedicinePercutaneous coronary interventionCardiologyCoronary artery diseaseArteryInternal medicineBypass graftingGuidelineMyocardial infarction

Abstract

fetched live from OpenAlex

Ever since the introduction of percutaneous coronary intervention (PCI) for the treatment of chronic coronary artery disease (CAD), there has been hope of curing CAD mechanically without exposing the patient to much more invasive coronary artery bypass surgery (CABG). Hefty controversies have created somewhat of a “battlefield of PCI and CABG” (see the EXCEL trial data controversy1), where different guideline interpretations and possibly other incentives resulted in ratios of PCI to CABG performance ranging from approximately 2:1 in one country to more than 10:1 in the next.

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)0.009
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.076
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.060
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.002
Science and technology studies0.0050.007
Scholarly communication0.0040.007
Open science0.0070.002
Research integrity0.0760.075
Insufficient payload (model declined to judge)0.0160.014

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 head0.029
GPT teacher head0.331
Teacher spread0.302 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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