{"id":"W192821","doi":"10.1007/978-3-642-41299-8_4","title":"A Scientometrics Study of Rough Sets in Three Decades","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Scientometrics; Computer science; Library science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.005213229,0.000345559,0.0007267583,0.02165996,0.001772506,0.004485558,0.0006714612,0.0008277686,0.00237742],"category_scores_gemma":[0.02825153,0.000278006,0.0008253032,0.05449564,0.002340606,0.005899942,0.001919551,0.00141447,0.0003435152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003635583,"about_ca_system_score_gemma":0.002871479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01022711,"about_ca_topic_score_gemma":0.00790209,"domain_scores_codex":[0.9980546,0.0005935931,0.0001597308,0.0001981624,0.000807238,0.0001866041],"domain_scores_gemma":[0.9860989,0.008851842,0.001666726,0.0007851004,0.001916385,0.0006810274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001713006,0.0001193585,0.04776685,0.0006347725,0.0002379943,0.00018242,0.00501527,0.005605375,0.0002179248,0.7262045,0.02187809,0.1919661],"study_design_scores_gemma":[0.00002717697,0.0002449464,0.3130094,0.001416103,0.0003044543,0.0005871061,0.009852468,0.01307123,0.0007290335,0.4139204,0.2467196,0.0001180249],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5801692,0.1528652,0.0205439,0.0337532,0.00156641,0.00008075833,0.003206763,0.0001774239,0.2076371],"genre_scores_gemma":[0.9517992,0.03541033,0.003339995,0.0004829526,0.001513724,0.00004443401,0.0007600829,0.00003821089,0.006611071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.97834,"threshold_uncertainty_score":0.02757055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04097173767765032,"score_gpt":0.2816243653013237,"score_spread":0.2406526276236733,"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."}}