{"id":"W2980455226","doi":"10.1161/circoutcomes.117.004351","title":"Buffer or Suffer","year":2018,"lang":"en","type":"article","venue":"Circulation Cardiovascular Quality and Outcomes","topic":"Heart Failure Treatment and Management","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"National Heart, Lung, and Blood Institute","keywords":"Buffer (optical fiber); Computer science; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.0007084984,0.0001416274,0.0004758493,0.00007739386,0.0001312493,0.00003045279,0.00002903751,0.0000794325,0.0002842265],"category_scores_gemma":[0.0001410998,0.00009606327,0.0004323212,0.0001311623,0.00009952082,0.00009477374,0.00003349468,0.0000588254,0.0001322675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004349853,"about_ca_system_score_gemma":0.00002974724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008624622,"about_ca_topic_score_gemma":0.00001631823,"domain_scores_codex":[0.9988,0.0001197901,0.0002469814,0.0002845473,0.0003688098,0.0001798861],"domain_scores_gemma":[0.999211,0.00006014261,0.00002929365,0.0004767047,0.0001048711,0.0001179729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001433834,0.0001264166,0.9352006,0.0002364138,0.004128634,0.00005341152,0.0005895422,0.000006790809,0.0001011083,0.005858748,0.00137379,0.05218121],"study_design_scores_gemma":[0.001619568,0.00005341618,0.8728507,0.00001590814,0.0004817392,0.00002325783,0.00008391731,0.00003919625,0.00008445766,0.0001456714,0.1244801,0.0001220975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746557,0.000857383,0.01093419,0.00746042,0.0003299314,0.0008572381,0.000003993048,0.0002048388,0.004696328],"genre_scores_gemma":[0.9956498,0.00005009096,0.001021014,0.00148349,0.0002326797,0.00001885799,0.00002213011,0.00001396285,0.001507994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1231063,"threshold_uncertainty_score":0.3917346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08960053229617991,"score_gpt":0.3543397250952042,"score_spread":0.2647391927990243,"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."}}