{"id":"W2958588221","doi":"","title":"Specifying Distinct Groups in Multivariate Data using Machine Learning","year":2019,"lang":"en","type":"article","venue":"MacEwan University Student Research Proceedings","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Multivariate statistics; Computer science; Artificial intelligence; Machine learning","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":[0.007489044,0.001094777,0.001328382,0.00214888,0.001425868,0.00394465,0.002329644,0.00239962,0.004169723],"category_scores_gemma":[0.03199593,0.0009256997,0.002551614,0.002076558,0.002234119,0.00732858,0.003688598,0.004598037,0.001055052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001305741,"about_ca_system_score_gemma":0.002102867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001704154,"about_ca_topic_score_gemma":0.002779821,"domain_scores_codex":[0.9904341,0.003978696,0.001183578,0.002191383,0.00171654,0.0004958786],"domain_scores_gemma":[0.9630702,0.02628569,0.001972121,0.006204246,0.001768472,0.0006992302],"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":[0.001515197,0.0007063225,0.02307266,0.000789954,0.0002029193,0.001194364,0.003009508,0.08336266,0.0138093,0.4161732,0.01294987,0.4432141],"study_design_scores_gemma":[0.0001366211,0.0001389019,0.001235378,0.0001216085,0.00006340276,0.0003098672,0.0006215649,0.4373366,0.007214585,0.5419378,0.01081879,0.00006491517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01487305,0.00005849298,0.9825757,0.00040848,0.00002762019,0.0001010054,0.0005012081,0.000887989,0.0005664505],"genre_scores_gemma":[0.1503929,0.00008423817,0.8455886,0.0002728359,0.00006446298,0.0004144241,0.002077782,0.000274444,0.0008303768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007489044,"threshold_uncertainty_score":0.03960633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2145727113577028,"score_gpt":0.3929637549346773,"score_spread":0.1783910435769744,"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."}}