{"id":"W3177635878","doi":"","title":"ペルシャンブルーで改質した感受性の高いインジウム・スズ酸化物電極についてのビスフェノール-Aの高性能電流測定検出法","year":2008,"lang":"ja","type":"article","venue":"Journal of New Materials for Electrochemical Systems","topic":"Military Technology and Strategies","field":"Engineering","cited_by":1,"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"],"consensus_categories":[],"category_scores_codex":[0.0008186662,0.0005948073,0.001629578,0.0002923382,0.000186092,0.0001009589,0.0007962928,0.0009283746,0.000168019],"category_scores_gemma":[0.000339509,0.0005375522,0.0004429018,0.0002798863,0.0001561097,0.000379547,0.00004737707,0.0006297195,0.00004953523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004208034,"about_ca_system_score_gemma":0.0004420641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005953995,"about_ca_topic_score_gemma":0.000002866694,"domain_scores_codex":[0.9958317,0.00009329183,0.002137853,0.0003366626,0.0005993783,0.001001139],"domain_scores_gemma":[0.9977877,0.0002194821,0.0007299139,0.0004085916,0.0004711229,0.0003832357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006331404,0.00008903992,0.00003083275,0.0007128083,0.0006250319,0.0001047221,0.0003749825,0.0001756268,0.942301,0.004205799,0.05068902,0.00005799099],"study_design_scores_gemma":[0.003226059,0.001811206,0.00009491049,0.0007250714,0.0003555994,0.007712701,0.0003367215,0.0003310151,0.9393784,0.006299317,0.03881129,0.0009176804],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9649041,0.02222051,0.004742755,0.0004109844,0.005090707,0.0007031042,0.0000683853,0.0001896613,0.001669851],"genre_scores_gemma":[0.991887,0.002412955,0.0005060278,0.00003286447,0.003916044,0.00002064481,0.00001788603,0.0001047052,0.001101906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02698292,"threshold_uncertainty_score":0.9997076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01602013584110457,"score_gpt":0.2266413684147595,"score_spread":0.210621232573655,"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."}}