{"id":"W4250401823","doi":"10.32920/ryerson.14668092","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; Computer science; Pregnancy; Nuclear medicine; Gestation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000163037,0.0001260116,0.0003881268,0.00007139506,0.00002466554,0.00002249482,0.00003155473,0.0001877504,0.00004005291],"category_scores_gemma":[0.00005561789,0.0001102733,0.00006786182,0.0000395613,0.00003056496,0.00005325627,0.00006859627,0.0001111609,1.81153e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001353668,"about_ca_system_score_gemma":0.0002147988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002693751,"about_ca_topic_score_gemma":7.76129e-7,"domain_scores_codex":[0.9992473,0.0000230458,0.0002579572,0.0002399942,0.0001279203,0.0001038393],"domain_scores_gemma":[0.9994524,0.00006823085,0.0001188767,0.0001468516,0.0001616419,0.00005197452],"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":[0.002542248,0.0004840397,0.001535483,0.007911785,0.0007054504,0.00001177429,0.03252862,0.2885531,0.5910537,0.001401008,0.00002635458,0.07324649],"study_design_scores_gemma":[0.000672518,0.00005334052,0.001398544,0.0002369914,0.0001330335,0.000002658297,0.0001155415,0.9896559,0.007265189,0.000335159,0.00003170755,0.00009942299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3799093,0.00005398626,0.6193587,0.000142241,0.00003032681,0.0004228115,0.00001727894,0.00002413952,0.00004114373],"genre_scores_gemma":[0.9377476,0.00006590761,0.06077687,0.0001817161,0.00007511054,0.00003544322,0.0004466805,0.00001905676,0.0006516075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7011029,"threshold_uncertainty_score":0.4496814,"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."}}