{"id":"W2139473768","doi":"10.5539/mas.v3n8p9","title":"Study on the Material Requisition System Based on Data Mining","year":2009,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shanghai Leading Academic Discipline Project","keywords":"Requisition; Production (economics); Computer science; Process (computing); Quality (philosophy); Data mining; Risk analysis (engineering); Business","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":[],"consensus_categories":[],"category_scores_codex":[0.001650169,0.0001376765,0.000112569,0.0001085513,0.0007960886,0.0007859575,0.004465287,0.00002257511,0.000002508815],"category_scores_gemma":[0.00002372195,0.00009449967,0.00001239233,0.0007355636,0.000101076,0.0003660988,0.0004064523,0.00009927611,0.00007250132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008544861,"about_ca_system_score_gemma":0.0001024966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005027603,"about_ca_topic_score_gemma":6.669664e-7,"domain_scores_codex":[0.9977192,0.00003341188,0.0001921754,0.000941624,0.0008032754,0.0003102648],"domain_scores_gemma":[0.9967312,0.00008860703,0.00009389871,0.002971283,0.00003576604,0.00007923911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006814965,0.001628662,0.0000298823,0.0000107092,0.000009639269,0.00002842644,0.004624856,0.002568691,0.135208,0.4453675,0.003127146,0.4073284],"study_design_scores_gemma":[0.000172393,0.0001708832,0.00143232,0.00002093668,0.000003554922,0.000001885665,0.000307052,0.9951116,0.002099917,0.0004554422,0.00009018973,0.0001338163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06974934,0.000001148427,0.9140199,0.001687539,0.0002289171,0.0006651481,0.00005505911,0.0003170641,0.01327583],"genre_scores_gemma":[0.9766022,8.218081e-8,0.02228722,0.0009502055,0.00007738835,0.0000513587,0.00001510242,0.00000487129,0.00001158188],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9925429,"threshold_uncertainty_score":0.8297688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06633616815029349,"score_gpt":0.2933465516805815,"score_spread":0.2270103835302881,"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."}}