{"id":"W7015263742","doi":"","title":"Statistical Analysis of Spherical Data:
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\\nApplications","year":2014,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Concordia University","keywords":"Feature (linguistics); Frame (networking); Probabilistic logic; Feature selection; Selection (genetic algorithm); Set (abstract data type)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000973139,0.0003005805,0.0007113739,0.001433743,0.0005510573,0.0002391868,0.002131615,0.0004481021,0.00002255116],"category_scores_gemma":[0.0001149672,0.0003229872,0.0001605302,0.003650062,0.0001979301,0.0004396807,0.0007557124,0.001139992,0.000004548979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002320157,"about_ca_system_score_gemma":0.0006356532,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.008787651,"about_ca_topic_score_gemma":0.03326405,"domain_scores_codex":[0.9959936,0.0009538824,0.0003262675,0.001360202,0.0008090986,0.0005569441],"domain_scores_gemma":[0.9968345,0.0005190512,0.0002883585,0.001621563,0.0003758091,0.0003607138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001686099,0.001251534,0.08710451,0.002024321,0.01098156,0.0008756749,0.003402853,0.0004413872,0.03062291,0.6818326,0.02584618,0.1539304],"study_design_scores_gemma":[0.001212667,0.001021343,0.6391614,0.0002071478,0.002959864,0.00006339628,0.0005041198,0.2646949,0.007210288,0.009547833,0.07173663,0.00168039],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05326608,0.0001317401,0.9219264,0.0002754942,0.0002754424,0.0003754699,0.00006039402,0.000100232,0.02358879],"genre_scores_gemma":[0.9113491,0.000279214,0.06108849,0.00001641228,0.0003161822,0.000008747269,0.0008678368,0.00004986491,0.0260242],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8608379,"threshold_uncertainty_score":0.9999222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02924071418218179,"score_gpt":0.3188399201044142,"score_spread":0.2895992059222324,"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."}}