{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001534369,0.0002708696,0.0001998137,0.001270041,0.002848104,0.004806697,0.0004148942,0.001105023,0.01580162],"category_scores_gemma":[0.003408022,0.0002119933,0.0002625675,0.001056877,0.005368758,0.003699795,0.0009670481,0.001464733,0.00365696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002316521,"about_ca_system_score_gemma":0.002287174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007527925,"about_ca_topic_score_gemma":0.007395852,"domain_scores_codex":[0.9987316,0.0001964383,0.0001091868,0.000240715,0.0005664061,0.0001557479],"domain_scores_gemma":[0.9984772,0.0003400253,0.0002049324,0.0001830737,0.0006684775,0.0001263007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000197154,0.00002088555,0.001351503,0.00004349134,0.00001042739,0.0001111279,0.001281205,0.0001543457,0.0005763099,0.9551263,0.00742545,0.03387927],"study_design_scores_gemma":[0.000016805,0.00008703936,0.009621259,0.0001422026,0.00004835621,0.0006653627,0.003255038,0.0009645324,0.004961662,0.6260214,0.3541499,0.00006650134],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04889075,0.003550872,0.02355823,0.008128577,0.001420418,0.0001347268,0.0003328233,0.00015663,0.9138269],"genre_scores_gemma":[0.7685108,0.002544931,0.0185024,0.001550233,0.0009069187,0.00008263871,0.0001792651,0.00005549074,0.2076674],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01580162,"threshold_uncertainty_score":0.05286175,"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."}}