{"id":"W6990011412","doi":"","title":"Classification of Missing Youths Cases using Support Vector Machines","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Set (abstract data type); Missing data; Interface (matter); Service (business); Intervention (counseling); Reduction (mathematics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003648001,0.0006702767,0.0008879044,0.003396763,0.0004442004,0.001055068,0.001103249,0.0005695006,0.001970262],"category_scores_gemma":[0.01423105,0.0002680281,0.00069826,0.001556455,0.0002281066,0.0008252159,0.0008161682,0.001088927,0.0008998639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000499321,"about_ca_system_score_gemma":0.001018647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006509004,"about_ca_topic_score_gemma":0.005268006,"domain_scores_codex":[0.9982621,0.0004681623,0.000245997,0.0002868847,0.0005082338,0.0002286679],"domain_scores_gemma":[0.9944252,0.00269325,0.0008569704,0.0005434756,0.001227768,0.0002533388],"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":[0.00140284,0.0007593685,0.415802,0.0001910915,0.0001879217,0.0007135393,0.0005471586,0.06657063,0.002374495,0.002466333,0.01229779,0.4966868],"study_design_scores_gemma":[0.00006146524,0.000384195,0.05637177,0.0001283619,0.00008102974,0.0002588726,0.0009594877,0.9280154,0.003797635,0.00678542,0.003123641,0.00003281611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7607914,0.0005922938,0.2295912,0.0009071447,0.0002540972,0.0002351576,0.004230391,0.001659854,0.001738444],"genre_scores_gemma":[0.9408938,0.0002074119,0.05309299,0.0000532471,0.0000817185,0.0001027685,0.00432348,0.00003585473,0.001208629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006509004,"threshold_uncertainty_score":0.01929271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05634667820165147,"score_gpt":0.3369673941658371,"score_spread":0.2806207159641856,"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."}}