{"id":"W6907714348","doi":"10.24433/co.3573560.v1","title":"Faust Ontology - Feature Vector Extraction and Clustering","year":2019,"lang":"en","type":"other","venue":"Code Ocean","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Cluster analysis; Pattern recognition (psychology); Feature extraction; Feature (linguistics); Support vector machine; FAUST; Fuzzy clustering","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008599033,0.0003425037,0.0004109618,0.0002721543,0.0000371713,0.00004964788,0.0001667821,0.0007264902,0.0006678317],"category_scores_gemma":[0.00003296722,0.0003423496,0.00005314427,0.00008675999,0.00007499092,0.00005933065,0.00008852337,0.0004858119,0.004170969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001212233,"about_ca_system_score_gemma":0.00003708591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000117928,"about_ca_topic_score_gemma":0.0019173,"domain_scores_codex":[0.9988334,0.00006402814,0.0001155648,0.0005194543,0.0001542528,0.0003133065],"domain_scores_gemma":[0.9991269,0.00003226888,0.000243486,0.0004861973,0.00002091416,0.00009030247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003892596,0.00001828513,0.0006291602,0.0001844389,0.0000749626,0.00002700401,0.0000664973,0.000003090167,0.0008589881,0.00008469033,0.9974009,0.0006130053],"study_design_scores_gemma":[0.0004906799,0.00003873912,0.001825503,0.0002179905,0.00007581175,0.0001311445,0.00003208722,0.0002167769,0.00002490953,0.000006599053,0.9965826,0.0003571879],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0006588438,0.003422612,0.0001877411,0.0001864791,0.002018905,0.0006473075,0.0005346366,0.0008768335,0.9914666],"genre_scores_gemma":[0.00765646,0.00008212362,0.0005962699,0.00007012594,0.0007622608,0.000002977317,0.0001646725,0.001586149,0.9890789],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.006997616,"threshold_uncertainty_score":0.9999028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.017977915482367,"score_gpt":0.2821194022951983,"score_spread":0.2641414868128313,"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."}}