{"id":"W2790095428","doi":"10.1002/sim.7611","title":"Discrimination surfaces with application to region‐specific brain asymmetry analysis","year":2018,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Morphological variations and asymmetry","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação para a Ciência e a Tecnologia; University of British Columbia; University of South Carolina; National Science Foundation","keywords":"Estimator; Statistic; Asymmetry; Brain asymmetry; Mathematics; Statistics; Confidence interval; Pattern recognition (psychology); Psychology; Computer science; Artificial intelligence; Cognitive psychology; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003329278,0.0004982477,0.0007265245,0.003208055,0.0003597992,0.001207753,0.0006587257,0.0007249374,0.001547883],"category_scores_gemma":[0.02152861,0.0002473489,0.0007375586,0.001627305,0.001338738,0.0009716256,0.001616077,0.001026233,0.0003220614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004706213,"about_ca_system_score_gemma":0.000468945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006570256,"about_ca_topic_score_gemma":0.000307551,"domain_scores_codex":[0.9988126,0.0004366713,0.00008230302,0.0001842048,0.0003943833,0.0000899302],"domain_scores_gemma":[0.9899149,0.007257949,0.0007498256,0.00087901,0.0009828395,0.0002154674],"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":[0.0004492778,0.000139657,0.02384834,0.0003201701,0.000175988,0.0006385245,0.0005695664,0.2318745,0.05713603,0.1711403,0.002948568,0.510759],"study_design_scores_gemma":[0.00002116754,0.000114593,0.01141586,0.00002598559,0.00002864858,0.000614949,0.00008867528,0.8707053,0.009109817,0.1051243,0.002693568,0.00005714058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03871562,0.0001641138,0.9594985,0.00009763963,0.00001903384,0.00004651505,0.0001158618,0.0004433786,0.0008992745],"genre_scores_gemma":[0.6669688,0.0002501334,0.3309373,0.00007405927,0.0001066521,0.0001522461,0.0004307524,0.0002824512,0.0007976193],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003329278,"threshold_uncertainty_score":0.01760709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04038446706239159,"score_gpt":0.3465978518653931,"score_spread":0.3062133848030015,"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."}}