{"id":"W2073888273","doi":"10.1016/s0002-8703(03)00437-x","title":"Optimizing glycoprotein IIb/IIIa receptor antagonist use for the non-ST–segment elevation acute coronary syndromes: risk stratification and therapeutic intervention","year":2003,"lang":"en","type":"review","venue":"American Heart Journal","topic":"Acute Myocardial Infarction Research","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Montreal Heart Institute","funders":"","keywords":"Medicine; Confusion; Antagonism; Blockade; Antagonist; Receptor antagonist; Receptor; Internal medicine; Risk stratification; Eptifibatide; Acute coronary syndrome; Pharmacology; Percutaneous coronary intervention; Cardiology; Myocardial infarction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001155124,0.0009455456,0.003354463,0.001275516,0.0001735337,0.0006882082,0.0009742192,0.001137679,0.001950718],"category_scores_gemma":[0.001649966,0.0002774071,0.000888176,0.00127695,0.0002209937,0.0006148029,0.0002567167,0.00125036,0.0005828519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004894967,"about_ca_system_score_gemma":0.001159578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001834463,"about_ca_topic_score_gemma":0.004592143,"domain_scores_codex":[0.9996383,0.0001012979,0.00006525372,0.00005245679,0.0001182235,0.00002441299],"domain_scores_gemma":[0.9993824,0.0003918591,0.0001000374,0.000009455325,0.00009415387,0.00002214592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004565321,0.0001550008,0.0005447837,0.01618583,0.0007197363,0.0001963945,0.00003008277,0.0004348214,0.0007055345,0.0006765171,0.01415083,0.9657439],"study_design_scores_gemma":[0.002321146,0.002341907,0.02114549,0.03477403,0.01001439,0.005405806,0.0002843927,0.001587672,0.002519008,0.004088588,0.9153947,0.0001228437],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003009996,0.9989057,0.0001436462,0.0002106219,0.00007290495,0.000009673772,0.00001273546,0.000004226303,0.0003395401],"genre_scores_gemma":[0.00224985,0.9966673,0.0004368809,0.000248763,0.0001481252,0.00001387614,0.00003231627,0.000001188801,0.0002015848],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003354463,"threshold_uncertainty_score":0.006525755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.087424551110498,"score_gpt":0.4029354982340722,"score_spread":0.3155109471235741,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}