{"id":"W3208187180","doi":"10.1002/cjs.11624","title":"Continuum centroid classifier for functional data","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Centroid; Classifier (UML); Pattern recognition (psychology); Binary classification; Artificial intelligence; Binary number; Computer science; Mathematics; Machine learning; Data mining; Algorithm; Support vector machine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.004453212,0.0009250327,0.002078773,0.004039403,0.001268372,0.002443193,0.003322115,0.003041695,0.003068823],"category_scores_gemma":[0.01630638,0.0003744778,0.001336033,0.003353347,0.002185904,0.003101765,0.002308546,0.003267109,0.002373412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001725978,"about_ca_system_score_gemma":0.001600945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003696806,"about_ca_topic_score_gemma":0.002293749,"domain_scores_codex":[0.9967879,0.0008202797,0.0001546045,0.0008080332,0.001202676,0.000226514],"domain_scores_gemma":[0.9950579,0.0021168,0.0004399756,0.0008496509,0.001228959,0.0003067944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005333945,0.0003033648,0.007764121,0.0003494709,0.0001571877,0.0004579735,0.0003177535,0.1798169,0.01124897,0.1621305,0.02379751,0.6131228],"study_design_scores_gemma":[0.00002086417,0.00006508668,0.001061054,0.00002736537,0.00001468388,0.0002041097,0.0000386284,0.9386474,0.002108798,0.05312829,0.004650933,0.00003257705],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008610395,0.0006080726,0.988197,0.0003380635,0.00009224957,0.00005690763,0.0001957414,0.0006178835,0.001283577],"genre_scores_gemma":[0.39707,0.001005433,0.5916618,0.0006032687,0.0006543439,0.0005697228,0.00207692,0.0003107417,0.006047665],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004453212,"threshold_uncertainty_score":0.02355111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08718200006104543,"score_gpt":0.2686054690282518,"score_spread":0.1814234689672063,"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."}}