{"id":"W245093286","doi":"","title":"コーポレート・レピュテーション測定上の課題 (特集 「企業の評判」の測定と管理--コーポレート・レピュテーション)","year":2011,"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":["insufficient_payload"],"category_scores_codex":[0.000869489,0.0009334623,0.0008646777,0.0005240219,0.0005647317,0.0001560476,0.001275346,0.00115868,0.003276039],"category_scores_gemma":[0.0002595394,0.001033847,0.0003493369,0.0008880746,0.0003978969,0.001366031,0.0003830922,0.001658128,0.002782699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001582381,"about_ca_system_score_gemma":0.00009798037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001001011,"about_ca_topic_score_gemma":0.000344275,"domain_scores_codex":[0.9956595,0.00008544407,0.001120141,0.00097597,0.0004473168,0.001711593],"domain_scores_gemma":[0.9978117,0.0002005563,0.0002465394,0.001365922,0.0001817084,0.0001935482],"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":[0.0005757362,0.001724302,0.1885711,0.005852074,0.005056781,0.003168388,0.06349094,0.002377944,0.02305842,0.5329673,0.05915825,0.1139987],"study_design_scores_gemma":[0.01113275,0.002238439,0.3206571,0.005422711,0.003429651,0.00179627,0.07725281,0.07731983,0.04591179,0.2459696,0.1876866,0.02118244],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5610962,0.008974358,0.0008508171,0.0002130329,0.002876888,0.0004859265,0.00004598537,0.00215878,0.423298],"genre_scores_gemma":[0.9927881,0.0008225284,0.003729685,0.000237056,0.0006971228,0.0000514117,0.00002916807,0.0001923034,0.001452674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4316919,"threshold_uncertainty_score":0.9992112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01797444090490192,"score_gpt":0.1988683711488357,"score_spread":0.1808939302439338,"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."}}