{"id":"W2347675945","doi":"","title":"An Inquiry Efficiency Enhancement Method Based on MIDAS in Enterprise Application","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Intranet; Enterprise management; Knowledge management; Process management; World Wide Web; The Internet","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"],"consensus_categories":[],"category_scores_codex":[0.0007043092,0.0002574479,0.0002010392,0.0004552293,0.0002231735,0.000109427,0.001465168,0.00009978069,0.000005778094],"category_scores_gemma":[9.554916e-7,0.0002765273,0.0000805923,0.001334244,0.00005272161,0.0002861671,0.0001438896,0.0002300271,0.00009589845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002163156,"about_ca_system_score_gemma":0.00007854203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001433573,"about_ca_topic_score_gemma":0.000008749044,"domain_scores_codex":[0.9976193,0.0000609184,0.0005832573,0.0009880353,0.0003135575,0.000434937],"domain_scores_gemma":[0.9981256,0.000244337,0.0001917408,0.001128942,0.0001386582,0.0001707589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001332398,0.001670561,0.0001720701,0.0000157506,0.000004936247,0.000002595794,0.0004306519,0.03999905,0.02611189,0.1447076,0.0001789937,0.7866925],"study_design_scores_gemma":[0.0005686127,0.000180898,0.003174675,0.00002832391,0.000005307075,0.000009498535,0.00002101339,0.8153706,0.03954284,0.02129119,0.1192975,0.0005095599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001199666,0.00002257476,0.995176,0.0007960867,0.00002156169,0.001560082,0.000004193961,0.0004397503,0.0007801208],"genre_scores_gemma":[0.2462775,0.00000303863,0.7504616,0.001764649,0.0001084995,0.001300889,0.00005184438,0.00001762519,0.00001432102],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7861829,"threshold_uncertainty_score":0.9999687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01248512154696868,"score_gpt":0.3495670273134827,"score_spread":0.337081905766514,"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."}}