{"id":"W7036771119","doi":"","title":"Classification study of rough sets generalization / by Han Yin Shi. --","year":2017,"lang":"en","type":"dissertation","venue":"Knowledge Commons (Lakehead University)","topic":"Digital Media and Philosophy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage; Library and Archives Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Lakehead University","keywords":"Rough set; Generalization; Feature (linguistics); Pattern recognition (psychology); Set (abstract data type)","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001990981,0.0004024925,0.0009471027,0.001464472,0.0009155065,0.001687682,0.0003983146,0.0003062369,0.004234234],"category_scores_gemma":[0.004021346,0.0002137685,0.001501752,0.002141702,0.001163971,0.001753965,0.000626264,0.001581336,0.0005989379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001873105,"about_ca_system_score_gemma":0.0008625687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004911843,"about_ca_topic_score_gemma":0.003020464,"domain_scores_codex":[0.9993036,0.0002167628,0.00004724694,0.0001992799,0.0001826569,0.00005044556],"domain_scores_gemma":[0.9984068,0.0007713812,0.00008210735,0.0001079113,0.0005547558,0.000077055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004133823,0.0001717146,0.01452549,0.001148698,0.000489346,0.0007145304,0.002377617,0.02490004,0.006481035,0.5844257,0.062335,0.3020174],"study_design_scores_gemma":[0.00006128728,0.0005146791,0.02543219,0.0003763489,0.0003987654,0.0008663188,0.002455952,0.289722,0.006357127,0.5598945,0.113747,0.000173821],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2465376,0.0452357,0.5681838,0.06510883,0.00821602,0.0003487389,0.001101443,0.0007725305,0.06449526],"genre_scores_gemma":[0.8584703,0.01403072,0.08012348,0.001892062,0.001962191,0.0002214405,0.0008949772,0.0001250799,0.04227976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004911843,"threshold_uncertainty_score":0.01416487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04876259098844647,"score_gpt":0.2786765843736565,"score_spread":0.22991399338521,"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."}}