{"id":"W2801362673","doi":"10.1089/soro.2017.0072","title":"A Dynamic Compliance Cervix Phantom Robot for Latent Labor Simulation","year":2018,"lang":"en","type":"article","venue":"Soft Robotics","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; McMaster University; University of Toronto","funders":"","keywords":"Imaging phantom; Cervix; Robot; Computer science; Soft palate; Mechatronics; Artificial intelligence; Simulation; Medicine; Medical physics; Surgery; Radiology","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":[0.0005753247,0.0003206518,0.0002763407,0.0002739713,0.0001381885,0.0002977097,0.0006554792,0.0004927083,0.003919259],"category_scores_gemma":[0.002076453,0.0002284028,0.0002690781,0.00009029072,0.0003280243,0.0003304639,0.0008361345,0.0003999397,0.0004782006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001964177,"about_ca_system_score_gemma":0.0007184134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003259196,"about_ca_topic_score_gemma":0.0002698399,"domain_scores_codex":[0.9997615,0.00008147466,0.0000138514,0.00002745955,0.00009824515,0.00001755673],"domain_scores_gemma":[0.9993827,0.0003494183,0.00006340648,0.00007955305,0.00004832164,0.00007646428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00147726,0.0006769457,0.004577935,0.0008779055,0.00005034144,0.001032261,0.0006825551,0.05773651,0.7868065,0.007362441,0.003201047,0.1355182],"study_design_scores_gemma":[0.0007242637,0.01529266,0.01816431,0.0003368383,0.0001506793,0.005657275,0.0003218182,0.5059584,0.3730996,0.003440512,0.07653302,0.0003205437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3366059,0.0008203425,0.6489343,0.0007536937,0.0002703887,0.0009861692,0.0004515912,0.003545237,0.007632336],"genre_scores_gemma":[0.8113885,0.0005043315,0.1804681,0.000235037,0.00003192818,0.0009864673,0.0003460908,0.0002022814,0.005837346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003919259,"threshold_uncertainty_score":0.01311129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08472667533294868,"score_gpt":0.3772051046703342,"score_spread":0.2924784293373855,"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."}}