{"id":"W2765146929","doi":"10.1063/1.4999939","title":"A statistical model of false negative and false positive detection of phase singularities","year":2017,"lang":"en","type":"article","venue":"Chaos An Interdisciplinary Journal of Nonlinear Science","topic":"Cardiac electrophysiology and arrhythmias","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Hôpital du Sacré-Cœur de Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"False positive paradox; Mathematics; Noise (video); False positives and false negatives; Range (aeronautics); Algorithm; Phase (matter); Monte Carlo method; False positive rate; Sensitivity (control systems); Pattern recognition (psychology); Statistical physics; Statistics; Artificial intelligence; Computer science; Physics; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005321243,0.0001063681,0.000424386,0.0001988943,0.000410153,0.00002746112,0.0001819228,0.0000510424,0.00000500579],"category_scores_gemma":[0.0003528417,0.00008178094,0.00009927809,0.00007817973,0.002317262,0.0005260084,0.0002447893,0.0002563124,3.646877e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003894705,"about_ca_system_score_gemma":0.0002607462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000669008,"about_ca_topic_score_gemma":0.000005142394,"domain_scores_codex":[0.9989525,0.00003945373,0.0003907466,0.0001743883,0.0002771206,0.0001658114],"domain_scores_gemma":[0.9983228,0.0000836269,0.0005415803,0.0002372603,0.00065394,0.0001607817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002704391,0.0004479722,0.0001863777,0.00005976589,0.00006341821,0.0001964688,0.003994683,0.0001550672,0.9718166,0.0004023064,0.000002350652,0.01997058],"study_design_scores_gemma":[0.004927435,0.01566676,0.04044944,0.000989026,0.0003136309,0.003586889,0.00372675,0.2475439,0.6692146,0.01331455,0.000001324919,0.0002656726],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861397,0.00008803954,0.01317089,0.0002282118,0.0001193543,0.00009459981,0.00006708239,0.000002739533,0.00008938157],"genre_scores_gemma":[0.9913737,0.00003128188,0.008404233,0.00001792675,0.0001461273,7.345855e-7,0.00000133842,0.000006725671,0.00001791832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.302602,"threshold_uncertainty_score":0.8538049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02481071358059932,"score_gpt":0.3719093891448755,"score_spread":0.3470986755642761,"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."}}