{"id":"W2004759662","doi":"10.1016/j.ins.2009.04.018","title":"Foundations of near sets","year":2009,"lang":"en","type":"article","venue":"Information Sciences","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":113,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Perception; Computer science; Artificial intelligence; Set (abstract data type); Mathematics; Representation (politics); Theoretical computer science; Pattern recognition (psychology); Epistemology","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":[0.0003267974,0.00003643242,0.00004990887,0.00008443611,0.0002117535,0.0003270756,0.0005469662,0.00001567795,0.00001331675],"category_scores_gemma":[0.00004095352,0.00002691206,0.00002143031,0.0006131134,0.0001002008,0.003650663,0.00003328113,0.0000236951,0.00009592142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006150485,"about_ca_system_score_gemma":0.00008379392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001259672,"about_ca_topic_score_gemma":8.050359e-7,"domain_scores_codex":[0.9993672,0.000009409647,0.000196331,0.00005704422,0.0002711193,0.00009887628],"domain_scores_gemma":[0.9996299,0.00002557847,0.0001080458,0.0001414396,0.00006823421,0.00002684469],"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":[6.897475e-7,0.00001731575,0.0002837112,0.000002866592,0.00000119135,1.552361e-7,0.003067129,0.002160021,0.00001957137,0.3147191,0.001622786,0.6781055],"study_design_scores_gemma":[0.0002480732,0.0004140141,0.06314582,0.00001501757,0.000001983692,0.00001521745,0.0002769279,0.8003661,0.0004295362,0.08075828,0.05412338,0.0002056278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04196361,0.00002699885,0.6604243,0.006296391,0.0003774897,0.000146654,0.000003127321,0.0001376666,0.2906238],"genre_scores_gemma":[0.904937,0.00000385582,0.09414779,0.000899121,0.000005049446,8.551712e-7,0.000001299743,1.871868e-7,0.000004898111],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8629733,"threshold_uncertainty_score":0.3153998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03531542003680307,"score_gpt":0.3034031405494786,"score_spread":0.2680877205126756,"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."}}