{"id":"W4233162832","doi":"10.32920/ryerson.14668092.v1","title":"Design and characterization of a cervical phantom model for birth simulation training","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Pelvic and Acetabular Injuries","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"McMaster University","keywords":"Imaging phantom; Cervical dilation; Cervix; Biomedical engineering; Materials science; Stress (linguistics); Medicine; Obstetrics; Computer science; Pregnancy; Nuclear medicine; Gestation; Biology; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005280904,0.0002964567,0.0002179547,0.000346684,0.0001727667,0.0005299657,0.0006590839,0.0007912929,0.002035139],"category_scores_gemma":[0.001302793,0.0003136072,0.0002296954,0.0002193519,0.0002737404,0.0002649826,0.0004046768,0.000282379,0.0004005901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003097656,"about_ca_system_score_gemma":0.0009923308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000600622,"about_ca_topic_score_gemma":0.0007263965,"domain_scores_codex":[0.9997713,0.00003347818,0.00001430039,0.00003401102,0.0001291283,0.00001780856],"domain_scores_gemma":[0.9994703,0.0002104099,0.00008459449,0.00007065399,0.000111261,0.00005273512],"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":[0.0002987818,0.0001520303,0.003529871,0.0004731061,0.00001857133,0.0005451783,0.0002409102,0.08418622,0.8769438,0.001871059,0.0009421583,0.03079821],"study_design_scores_gemma":[0.00009730877,0.002418439,0.01200027,0.0001546846,0.0001152276,0.001789656,0.0002499653,0.39068,0.5592933,0.001031311,0.03202374,0.0001461458],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5562112,0.001245368,0.4289879,0.0008338649,0.0002111805,0.001140204,0.001655659,0.001003253,0.00871139],"genre_scores_gemma":[0.8506528,0.0009671118,0.1400959,0.0001481683,0.00001372178,0.0007316961,0.0008395361,0.0001118862,0.006439233],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002035139,"threshold_uncertainty_score":0.006808221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09360286641294842,"score_gpt":0.3297119244995975,"score_spread":0.2361090580866491,"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."}}