{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005245824,0.0007038296,0.0005730391,0.001286743,0.0003476405,0.0007098574,0.001282344,0.0008650305,0.00227446],"category_scores_gemma":[0.01013771,0.0002464066,0.0004871057,0.0004632882,0.000426857,0.0006645853,0.0006766755,0.000513823,0.00130643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005233587,"about_ca_system_score_gemma":0.000797675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008787761,"about_ca_topic_score_gemma":0.0008981464,"domain_scores_codex":[0.9968945,0.001229116,0.0002183019,0.000531907,0.001017663,0.0001085014],"domain_scores_gemma":[0.9920747,0.002923227,0.0008731318,0.0008617184,0.003085437,0.0001817174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002281242,0.0005097843,0.03363691,0.0004428019,0.0001846551,0.0004719199,0.0004697869,0.008066172,0.1694224,0.0007936982,0.004788931,0.7789317],"study_design_scores_gemma":[0.001389188,0.007227645,0.1256609,0.0002608223,0.0006705684,0.009923007,0.0003375832,0.5234526,0.3003468,0.002566151,0.02772667,0.0004380403],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1518683,0.0005666669,0.8403113,0.0002039279,0.0001222461,0.0006747964,0.0001933701,0.004913717,0.001145671],"genre_scores_gemma":[0.4262871,0.0001789238,0.5706992,0.0002860768,0.0001099401,0.0006524727,0.0004178986,0.0002973036,0.001071162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005245824,"threshold_uncertainty_score":0.02774286,"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."}}