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Record W2902817646 · doi:10.1007/s12265-018-9846-5

Sex and Gender Differences in Ischemic Heart Disease: Endocrine Vascular Disease Approach (EVA) Study Design

2018· article· en· W2902817646 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Cardiovascular Translational Research · 2018
Typearticle
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsMcGill University Health Centre
FundersUniversità degli Studi di FerraraSapienza Università di RomaMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsDiseaseMedicineInternal medicineEndocrine systemCardiologyHormone

Abstract

fetched live from OpenAlex

Improvements in ischemic heart disease (IHD) management have been unbalanced between sexes, with coronary microvascular dysfunction considered the likely underlying reason. The Endocrine Vascular disease Approach (EVA) is an observational study (Clinicaltrial.gov NCT02737982) aiming to assess sex and gender interactions between coronary circulation, sexual hormones, and platelet function. Consecutive patients with IHD undergoing coronary angiography will be recruited: (1) to assess sex and gender differences in angiographic reperfusion indexes; (2) to evaluate the effects of estrogen/androgen on sex-related differences in myocardial ischemia; (3) to investigate the platelet biology differences between men and women with IHD; (4) to verify sex- and gender-driven interplay between response to percutaneous coronary intervention, platelets, sex hormones, and myocardial damage at baseline and its impact on 12-month outcomes. The integration of sex and gender in this translational project on IHD will contribute to the identification of new targets for further innovative clinical interventions.

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.

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.260
GPT teacher head0.415
Teacher spread0.156 · 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