{"id":"W2626387068","doi":"","title":"トピックス：iPS細胞の目指す方向性；血小板産生系を例に","year":2012,"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005542507,0.0003717317,0.0003811548,0.0001668684,0.0001542939,0.00001615563,0.000484149,0.000427102,0.009345356],"category_scores_gemma":[0.0001188472,0.0003702913,0.0001304125,0.0002986832,0.0002930274,0.0004436174,0.0001067315,0.001019688,0.002896451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007159171,"about_ca_system_score_gemma":0.00004571259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003060839,"about_ca_topic_score_gemma":0.000004066601,"domain_scores_codex":[0.9978071,0.00007344949,0.0004239604,0.000259369,0.0003536924,0.001082381],"domain_scores_gemma":[0.9988397,0.0001405171,0.00004889565,0.0004723387,0.00002801989,0.000470504],"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":[0.0001676121,0.001282323,0.01492145,0.002366452,0.002336943,0.0003964467,0.01910852,0.0003498733,0.0162442,0.1384413,0.6568596,0.1475253],"study_design_scores_gemma":[0.002108233,0.0001310868,0.004695299,0.0002509615,0.0004477102,0.0002464852,0.002504624,0.006806657,0.01035204,0.004119732,0.9670063,0.001330899],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2261074,0.1464025,0.001103921,0.004220742,0.01317128,0.0005542314,0.0001079783,0.00231188,0.6060201],"genre_scores_gemma":[0.9919979,0.004307698,0.0005453911,0.0003407705,0.001608201,0.0000372877,0.00002645174,0.00005662282,0.00107971],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7658905,"threshold_uncertainty_score":0.9998749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091177422792521,"score_gpt":0.2658835149053504,"score_spread":0.2449717406774252,"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."}}