{"id":"W2165275868","doi":"","title":"Deletion and Addition Methods for Reduct Construction","year":2014,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Rogers Communications (Canada); University of Regina","funders":"","keywords":"Reduct; Construct (python library); Order (exchange); Mathematics; Computer science; Data mining; Natural language processing; Artificial intelligence; Rough set; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.004794603,0.001220384,0.0009804809,0.002878642,0.001584435,0.003238765,0.002519906,0.0009223463,0.007480436],"category_scores_gemma":[0.01559765,0.0008877867,0.002545933,0.002055608,0.00450617,0.005364036,0.004156429,0.003460584,0.001760181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001578999,"about_ca_system_score_gemma":0.001429407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001432442,"about_ca_topic_score_gemma":0.001591787,"domain_scores_codex":[0.9934957,0.002001258,0.0005765778,0.001509452,0.002076661,0.0003404011],"domain_scores_gemma":[0.9888306,0.006575018,0.0003522886,0.002741513,0.001310601,0.0001900048],"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":[0.000114663,0.00008021731,0.0005520803,0.0003996121,0.00005627739,0.00008818092,0.0005663249,0.01109511,0.003375396,0.7374492,0.003512728,0.2427102],"study_design_scores_gemma":[0.00006114923,0.0001008002,0.0003462979,0.0001709087,0.0001434182,0.0003709516,0.0002874575,0.08854,0.02466985,0.8394793,0.04574724,0.00008264973],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004732761,0.0003101031,0.987242,0.0001976636,0.00008834079,0.0001171149,0.00008082599,0.0007528306,0.006478384],"genre_scores_gemma":[0.1373177,0.0005027722,0.8506182,0.0002091526,0.000106373,0.0002870672,0.0004373784,0.0009494875,0.009571986],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007480436,"threshold_uncertainty_score":0.02535653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03662091824728102,"score_gpt":0.3131161217739451,"score_spread":0.2764952035266641,"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."}}