{"id":"W2747259386","doi":"","title":"EXPERT MEETING 2006 血管機能からみた高血圧治療","year":2006,"lang":"ja","type":"article","venue":"Pharma Medica","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001605263,0.0007635029,0.0004396101,0.0005955819,0.0007924931,0.001325601,0.0007961899,0.005104388,0.04709084],"category_scores_gemma":[0.002007041,0.0002432335,0.0006241653,0.0003028325,0.0003906437,0.0008117247,0.0005977497,0.001881024,0.0149909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009150164,"about_ca_system_score_gemma":0.001767799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001563753,"about_ca_topic_score_gemma":0.005440501,"domain_scores_codex":[0.9994668,0.00007682187,0.00005037755,0.00005208329,0.0002486722,0.0001052286],"domain_scores_gemma":[0.9988868,0.0001668378,0.00005197404,0.0000357379,0.0006237049,0.0002350779],"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":[0.0001585909,0.00007515514,0.0002943027,0.0005866853,0.00001970541,0.0006228783,0.00006034637,0.00008998858,0.002781262,0.001436744,0.868032,0.1258423],"study_design_scores_gemma":[0.00002153181,0.00005104369,0.0004066431,0.0001323645,0.00001430195,0.0006222192,0.00004018109,0.00006017165,0.000626749,0.0004965298,0.9975219,0.000006276138],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01124798,0.101689,0.006783531,0.2955605,0.2644354,0.0006882478,0.001237833,0.0003307555,0.3180268],"genre_scores_gemma":[0.04103567,0.06438955,0.009427215,0.04938317,0.05602351,0.0003485059,0.001503556,0.0001088715,0.7777799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04709084,"threshold_uncertainty_score":0.1575345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01266322053612463,"score_gpt":0.2503270853856836,"score_spread":0.237663864849559,"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."}}