{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001148532,0.0001204392,0.0002130329,0.00004921043,0.0001191872,0.00002089754,0.00005512671,0.00008554196,0.0001522602],"category_scores_gemma":[0.00018126,0.0001065687,0.00008370247,0.0001924901,0.00007298247,0.00005298697,0.0000190356,0.00008484692,0.0001142087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000653848,"about_ca_system_score_gemma":0.00003870177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000036673,"about_ca_topic_score_gemma":0.00001416394,"domain_scores_codex":[0.999116,0.00001375378,0.0002343443,0.0002125404,0.0001761101,0.0002472328],"domain_scores_gemma":[0.9990419,0.0002613779,0.00007226529,0.0001838139,0.0003167279,0.0001239302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005420399,0.0002352391,0.02083477,0.0001532394,0.00009745136,0.00001037043,0.0004484068,0.9349329,0.0004437352,0.001782932,0.00006111661,0.04045784],"study_design_scores_gemma":[0.003009637,0.0002337116,0.04307975,0.00008785101,0.00006789447,0.000003389249,0.00002538316,0.9467099,0.0000573651,0.0005505306,0.006049323,0.0001252382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0857742,0.0001822264,0.9068117,0.002780883,0.0009138405,0.001080043,0.00002924806,0.0003968539,0.002031054],"genre_scores_gemma":[0.9698821,0.000004293493,0.02783546,0.001018836,0.0002202327,0.000007573462,0.0000686383,0.00002749597,0.0009353322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8841079,"threshold_uncertainty_score":0.4345746,"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."}}