{"id":"W3006288522","doi":"10.1016/j.jcin.2019.11.030","title":"When SVGs “Had Enough”","year":2020,"lang":"en","type":"letter","venue":"JACC: Cardiovascular Interventions","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0005607393,0.0006362586,0.00113821,0.0004395816,0.0002603776,0.0009081725,0.004295886,0.000781478,0.0001718069],"category_scores_gemma":[0.000273826,0.0006185307,0.007600839,0.0006289865,0.000107555,0.0007619364,0.001673694,0.003157744,0.0006161707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000234612,"about_ca_system_score_gemma":0.000141708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001333664,"about_ca_topic_score_gemma":0.000005464703,"domain_scores_codex":[0.9952819,0.0005221519,0.0007798048,0.00143461,0.001303201,0.0006782954],"domain_scores_gemma":[0.996102,0.00009183531,0.0003120849,0.003020908,0.000337868,0.0001353502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[7.372404e-7,0.00002485658,0.000001157538,0.0006636141,0.001631878,0.001765011,0.0001693856,0.000002456764,0.000006726914,0.001418339,0.9665088,0.027807],"study_design_scores_gemma":[0.0002032698,0.00007066769,0.000003079475,0.0008191236,0.0004924793,0.0002395021,0.000005391511,0.0001514251,0.0004098986,0.02298394,0.9739303,0.0006909231],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[4.764708e-7,0.04086444,0.5736399,0.3811976,0.0009789193,0.000423899,0.00004064533,0.001690459,0.001163567],"genre_scores_gemma":[0.0004692298,0.000222018,0.5067869,0.481131,0.005007349,0.0004001389,0.0004282555,0.0001824387,0.005372581],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0999334,"threshold_uncertainty_score":0.9996266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03340529118534909,"score_gpt":0.2747619510714959,"score_spread":0.2413566598861468,"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."}}