{"id":"W422559817","doi":"","title":"債務超過の検出法則(第一類型)--架空資産計上の傍証固めから切り込む","year":2006,"lang":"ja","type":"article","venue":"Accounting","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":[0.001388191,0.0002505998,0.0001883826,0.001023744,0.002444314,0.004933931,0.0003767609,0.00097911,0.01743315],"category_scores_gemma":[0.003241295,0.0002047824,0.0002354306,0.0009107747,0.004836368,0.003318136,0.0007982399,0.001274929,0.00379116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002346302,"about_ca_system_score_gemma":0.002216596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005966369,"about_ca_topic_score_gemma":0.005209906,"domain_scores_codex":[0.9989994,0.0001376598,0.00007492906,0.0001804734,0.0004849262,0.0001225751],"domain_scores_gemma":[0.9984675,0.0003462187,0.0001750277,0.0001869332,0.0006948039,0.0001295978],"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":[0.00002443381,0.00002606891,0.001297207,0.00003911086,0.000008552627,0.00009813229,0.001185781,0.0001820218,0.0007106662,0.9604501,0.006153002,0.02982483],"study_design_scores_gemma":[0.00002149683,0.00009923828,0.009233949,0.0001314443,0.00004322201,0.0005679317,0.003468505,0.001329374,0.007128322,0.6460923,0.3318262,0.00005812282],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06519976,0.002730036,0.02200088,0.008706768,0.001216471,0.000131607,0.0002919364,0.0001504837,0.899572],"genre_scores_gemma":[0.8108061,0.001748313,0.01507643,0.001186201,0.0005738275,0.00006986618,0.0001547954,0.00004917491,0.1703353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01743315,"threshold_uncertainty_score":0.05831963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005168096426586608,"score_gpt":0.1890470024088708,"score_spread":0.1838789059822842,"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."}}