{"id":"W2920267096","doi":"","title":"A context-aware machine learning-based approach","year":2018,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Context (archaeology); Artificial neural network; Set (abstract data type); Context model; Control (management)","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":[0.001118451,0.001452098,0.001304682,0.001077511,0.0005648045,0.001317241,0.002317279,0.001373472,0.001759534],"category_scores_gemma":[0.003442184,0.0005955314,0.001029522,0.0008221806,0.0005532533,0.00226959,0.001648919,0.001755228,0.0006648574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007397629,"about_ca_system_score_gemma":0.001387054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004689837,"about_ca_topic_score_gemma":0.006511731,"domain_scores_codex":[0.9986795,0.000317707,0.00007684661,0.0004734795,0.0003328343,0.0001196358],"domain_scores_gemma":[0.9987551,0.0004293415,0.000121701,0.0002954788,0.0003213954,0.00007701501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002563265,0.0003683594,0.004262035,0.0002897547,0.0002720609,0.0003083249,0.0002178013,0.6301407,0.01720989,0.007759182,0.003014308,0.3359013],"study_design_scores_gemma":[0.000009614771,0.00006856229,0.0004241805,0.00001819418,0.00004968675,0.00006751858,0.00002771562,0.987999,0.003615145,0.005710802,0.00199153,0.00001802304],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0249196,0.001177668,0.9675562,0.000427386,0.0001210382,0.0001291776,0.0001289869,0.003077446,0.002462478],"genre_scores_gemma":[0.569322,0.0006496545,0.4258012,0.0005338851,0.0001625691,0.0002314759,0.0003584416,0.0003264572,0.002614204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004689837,"threshold_uncertainty_score":0.009325087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01083987578725308,"score_gpt":0.211665959954587,"score_spread":0.200826084167334,"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."}}