{"id":"W7131914002","doi":"","title":"信息不对称、会计稳健性与集团信贷模式","year":2015,"lang":"","type":"article","venue":"CEIBS Institutional Repository","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Casa","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004270947,0.000573166,0.0005554571,0.002874319,0.007812791,0.01290601,0.001353092,0.00226501,0.0108274],"category_scores_gemma":[0.009051436,0.0003786515,0.0005527736,0.004572334,0.01578022,0.01482909,0.002376745,0.002729371,0.001213231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01104987,"about_ca_system_score_gemma":0.01884758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02592894,"about_ca_topic_score_gemma":0.02057634,"domain_scores_codex":[0.9968209,0.001254952,0.0001528511,0.0005604091,0.0008972139,0.0003137331],"domain_scores_gemma":[0.9958682,0.002117079,0.00035061,0.0001799355,0.001055497,0.0004287493],"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":[0.000006460981,0.00001984365,0.0007079068,0.00006456377,0.000007525775,0.00005039676,0.009437592,0.0003242796,0.00006163363,0.9775831,0.003747339,0.007989519],"study_design_scores_gemma":[0.0000252671,0.00002041203,0.001663051,0.0002135836,0.00002932553,0.00008379832,0.04099201,0.00109826,0.0003285508,0.8651801,0.09033619,0.00002947936],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07557662,0.005757386,0.02272814,0.0513142,0.0008155056,0.0002068705,0.000336145,0.0001739847,0.8430911],"genre_scores_gemma":[0.939286,0.00339683,0.0109754,0.002727633,0.000346833,0.0002662987,0.0001090713,0.00004637906,0.04284548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02592894,"threshold_uncertainty_score":0.08017278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02040375174258996,"score_gpt":0.2189167139482475,"score_spread":0.1985129622056575,"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."}}