{"id":"W586879493","doi":"","title":"法規制からみた融資先支援条項の留意点 (特集 連結範囲のグレーゾーンを考える)","year":2008,"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002766399,0.0004163736,0.0004248307,0.000219454,0.0005397022,0.00004761609,0.0004966422,0.0005282474,0.0006804961],"category_scores_gemma":[0.0001320834,0.0004640027,0.0001597603,0.0004664531,0.0002609791,0.0006038191,0.0001356464,0.0008699653,0.001327551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008289514,"about_ca_system_score_gemma":0.0000640689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002229872,"about_ca_topic_score_gemma":0.00004816233,"domain_scores_codex":[0.9979227,0.00002891164,0.0005293738,0.000440356,0.0002588208,0.0008198988],"domain_scores_gemma":[0.9990136,0.0001291219,0.00008390113,0.0006181328,0.00007970577,0.00007554953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002310612,0.0009756712,0.3002324,0.004059696,0.003191492,0.006473175,0.04026816,0.03472761,0.03991575,0.3287936,0.1722762,0.06885513],"study_design_scores_gemma":[0.007259089,0.0008862037,0.3756374,0.002197881,0.0008711269,0.004581867,0.02313264,0.1577272,0.01732521,0.05856035,0.3404472,0.01137381],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8001381,0.009829834,0.0004003543,0.0003240048,0.001205571,0.0001797189,0.00001274359,0.001127078,0.1867826],"genre_scores_gemma":[0.9952499,0.001487373,0.001288693,0.0001414862,0.000523805,0.00001512411,0.00001292296,0.00007288981,0.001207863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2702333,"threshold_uncertainty_score":0.9997812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01201208805186526,"score_gpt":0.2004281490531616,"score_spread":0.1884160610012963,"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."}}