{"id":"W4282927708","doi":"10.1111/nmo.14421","title":"An automated artifact detection and rejection system for body surface gastric mapping","year":2022,"lang":"en","type":"article","venue":"Neurogastroenterology & Motility","topic":"Gastrointestinal motility and disorders","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Health Research Council of New Zealand; Royal Australasian College of Surgeons","keywords":"Artifact (error); Body surface; Computer vision; Computer science; Artificial intelligence; Mathematics; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.0005527107,0.0002100323,0.0003512252,0.0001527858,0.0004610467,0.00002216888,0.00009588544,0.00005574178,0.00002319229],"category_scores_gemma":[0.0001304119,0.0002341279,0.0001121803,0.0002099912,0.0001086206,0.0001300009,0.00007951383,0.0004084648,0.000002469487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001746745,"about_ca_system_score_gemma":0.00003111901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009967468,"about_ca_topic_score_gemma":0.00004357172,"domain_scores_codex":[0.9978412,0.0004586722,0.0003809084,0.0006501753,0.0001992595,0.0004697184],"domain_scores_gemma":[0.999092,0.00007234474,0.0001567933,0.0003771349,0.0001011013,0.0002006558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009506194,0.0005882899,0.8884695,0.0002510256,0.00004325609,0.00003312526,0.00009685798,0.001470121,0.1069462,0.00000382132,0.00006275732,0.001084441],"study_design_scores_gemma":[0.002036631,0.005647738,0.863633,0.00001185974,0.00008558472,0.001797946,0.0006484065,0.1255709,0.0004201694,0.0000108306,0.000111056,0.00002586477],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857042,0.00001410728,0.0116398,0.0004419974,0.0003857783,0.0009087982,0.00004410305,0.0008358314,0.00002532147],"genre_scores_gemma":[0.998476,0.000001059976,0.001002778,0.0003069066,0.00003947577,0.00008248355,0.00005399354,0.00002536437,0.0000119359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1241008,"threshold_uncertainty_score":0.9547458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622262504805001,"score_gpt":0.2648100906303362,"score_spread":0.2485874655822862,"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."}}