{"id":"W2748918274","doi":"","title":"がんのバイオマーカー:さらなる早期発見と的確な治療薬選択を目指して がん細胞由来細胞外遊離DNAの最新の知見と肺がんへの臨床応用","year":2016,"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":[0.0009580262,0.000233163,0.0001914505,0.0006732582,0.001326369,0.002983984,0.0003743236,0.001040653,0.009364508],"category_scores_gemma":[0.002435069,0.0002059134,0.0002008553,0.0004658712,0.003941502,0.002420668,0.0006963209,0.001063387,0.002736081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484219,"about_ca_system_score_gemma":0.001914532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002153655,"about_ca_topic_score_gemma":0.001550299,"domain_scores_codex":[0.9993708,0.0001284309,0.00003662055,0.0001567704,0.000257021,0.00005055704],"domain_scores_gemma":[0.9986771,0.0004588025,0.0001658897,0.00009422607,0.0004680733,0.0001358653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001558866,0.0001089774,0.00467481,0.0005334993,0.0000628314,0.0005615876,0.005857645,0.001371361,0.03779823,0.7543035,0.01428254,0.1802892],"study_design_scores_gemma":[0.00005662573,0.0003811024,0.008376749,0.0003201568,0.0001151044,0.001391299,0.00777562,0.001879276,0.07464218,0.3790567,0.5258545,0.0001507642],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.1652072,0.01689134,0.07705794,0.03012874,0.004415353,0.0002978884,0.0007153923,0.0003091187,0.704977],"genre_scores_gemma":[0.7685557,0.006787358,0.02827836,0.004182152,0.0009808401,0.0001929813,0.0001849177,0.00006310833,0.1907746],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.009364508,"threshold_uncertainty_score":0.03132743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01577333773784827,"score_gpt":0.2529153586427315,"score_spread":0.2371420209048832,"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."}}