{"id":"W3120475869","doi":"","title":"ДОКЛИНИЧЕСКИЕ МАРКЕРЫ МИОКАРДИАЛЬНОГО РЕМОДЕЛИРОВАНИЯ У МОЛОДЫХ БОЛЬНЫХ ГЕНЕТИЧЕСКИ ИНДУЦИРОВАННОЙ ГИПЕРТОНИЧЕСКОЙ БОЛЕЗНЬЮ","year":2020,"lang":"ru","type":"article","venue":"Молодежный инновационный вестник","topic":"Diet and metabolism studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002915596,0.0005067207,0.0004107963,0.002179199,0.00358229,0.008106618,0.0008222237,0.001492406,0.03306513],"category_scores_gemma":[0.007234613,0.0005226767,0.0006468382,0.002697882,0.004215914,0.003894201,0.003307909,0.001967589,0.009351247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004096196,"about_ca_system_score_gemma":0.008346594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01107984,"about_ca_topic_score_gemma":0.01337557,"domain_scores_codex":[0.9955511,0.001301514,0.0002368452,0.0006680114,0.001716282,0.0005261946],"domain_scores_gemma":[0.9963547,0.001207097,0.0004179137,0.0005148518,0.001087962,0.0004174215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002118749,0.0001746703,0.02187511,0.0008597802,0.00008153267,0.00132395,0.02984497,0.001237893,0.006302812,0.5850209,0.03541667,0.3176498],"study_design_scores_gemma":[0.00003857677,0.0000792291,0.02664881,0.0006412602,0.00007754684,0.001309181,0.02110676,0.0009329903,0.004218904,0.1098207,0.8350071,0.0001189769],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1512011,0.01361564,0.04306815,0.01730065,0.001080671,0.0002963327,0.001144652,0.0003929528,0.7718999],"genre_scores_gemma":[0.839274,0.01033329,0.02792433,0.001468998,0.0003530878,0.0004251377,0.0008394134,0.000306283,0.1190755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03306513,"threshold_uncertainty_score":0.1106139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04124858004561616,"score_gpt":0.2834922081311447,"score_spread":0.2422436280855285,"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."}}