{"id":"W2957648571","doi":"","title":"Support Vector Machine with Graphical Network Structures in Features","year":2019,"lang":"en","type":"article","venue":"Machine Learning and Data Mining in Pattern Recognition","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Western University","funders":"","keywords":"Computer science; Support vector machine; Graphical model; Theoretical computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004078398,0.0001571872,0.0001891268,0.0001185784,0.00008337842,0.0001481596,0.0004139189,0.00006729522,0.00005070931],"category_scores_gemma":[0.00002344686,0.0001276431,0.00001411525,0.0003956895,0.00002621051,0.0003279309,0.0003236961,0.0005351691,0.00001113026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008583965,"about_ca_system_score_gemma":0.00001285997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003147112,"about_ca_topic_score_gemma":0.001070446,"domain_scores_codex":[0.9986298,0.0001436423,0.0002037771,0.0005947892,0.0001490074,0.000278991],"domain_scores_gemma":[0.999261,0.0001921029,0.00009406267,0.0003820595,0.00001463388,0.00005620684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002022363,0.00002324311,0.6677421,0.00001929531,0.000006434879,0.00002344202,0.0001294304,0.0007182303,0.0000219006,0.00006089875,0.0001838311,0.3310509],"study_design_scores_gemma":[0.001174291,0.0002924938,0.6406566,0.0002176968,0.00001083052,0.0001438832,0.00003883907,0.3540633,0.00001431603,0.0008192564,0.002165983,0.0004025331],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9719405,0.0003138496,0.02571827,0.001028107,0.0001613556,0.0002822475,0.00006298874,0.0001199476,0.0003727195],"genre_scores_gemma":[0.990121,0.00007325671,0.008194249,0.0003401716,0.00008443142,0.0000141396,0.001115047,0.00001422563,0.00004349871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3533451,"threshold_uncertainty_score":0.5205136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01844727399585286,"score_gpt":0.2645528993714113,"score_spread":0.2461056253755584,"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."}}