{"id":"W1131999718","doi":"10.1007/s13042-015-0407-9","title":"Multigranulation decision-theoretic rough sets in incomplete information systems","year":2015,"lang":"en","type":"article","venue":"International Journal of Machine Learning and Cybernetics","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Rough set; Computational intelligence; Dominance-based rough set approach; Computer science; Mathematics; Data mining; Decision rule; Decision system; Set (abstract data type); Artificial intelligence; Operations research","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008445828,0.0000918872,0.0001459602,0.0002746844,0.00002973062,0.0002970449,0.0004199366,0.00005008962,0.000002851008],"category_scores_gemma":[0.0004032045,0.00007335072,0.00003557658,0.0001232933,0.00002621576,0.0006458997,0.0001207391,0.0002862085,0.00001002594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006670178,"about_ca_system_score_gemma":0.0000453845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001416675,"about_ca_topic_score_gemma":0.000009192655,"domain_scores_codex":[0.9986101,0.000114798,0.0005058138,0.0000822201,0.0005817896,0.0001052537],"domain_scores_gemma":[0.9988973,0.000171725,0.0003714596,0.00007246646,0.0003950651,0.00009203675],"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":[0.0002090049,0.000112893,0.1138146,0.0000171127,0.00006537458,0.0001362035,0.007889758,0.348265,0.00001571292,0.05441583,0.0004272719,0.4746312],"study_design_scores_gemma":[0.001593331,0.0002125059,0.01606632,0.0001131916,0.000005253562,0.0004377752,0.000141543,0.9465846,0.000003855679,0.01024389,0.02447827,0.0001194917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5050842,0.001988388,0.4841567,0.001837653,0.002671112,0.0001484557,0.000006828358,0.0000456186,0.004061051],"genre_scores_gemma":[0.9798737,0.0001829659,0.01974784,0.00008787613,0.00008105118,7.871281e-7,0.000007444975,0.000003794154,0.00001450885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5983196,"threshold_uncertainty_score":0.2991155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01349863090192814,"score_gpt":0.2684745414414522,"score_spread":0.2549759105395241,"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."}}