{"id":"W2913235541","doi":"10.1016/j.ejogrb.2019.01.007","title":"Impact of in vitro fertilization-preimplantation genetic testing (IVF-PGT) funding policy on clinical outcome: An issue that stems beyond effectiveness of treatment","year":2019,"lang":"en","type":"article","venue":"European Journal of Obstetrics & Gynecology and Reproductive Biology","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre; McGill University","funders":"McGill University Health Centre","keywords":"Infertility; Aneuploidy; In vitro fertilisation; Medicine; Reproductive medicine; Genetic testing; Chromosomal translocation; Preimplantation genetic diagnosis; Gynecology; Embryo transfer; Assisted reproductive technology; Pregnancy; Embryo; Genetic counseling; Sperm; Pregnancy rate; Andrology; Internal medicine; Chromosome; Genetics; Biology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001886651,0.0001634879,0.0007426321,0.0005792108,0.00003185605,0.000004457485,0.0001022667,0.000107188,0.000005905335],"category_scores_gemma":[0.01710415,0.0001121869,0.0001196657,0.0004020942,0.000173341,0.00006489113,0.00004539802,0.0002658485,0.000003510717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002080491,"about_ca_system_score_gemma":0.0002274226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005631776,"about_ca_topic_score_gemma":8.156404e-7,"domain_scores_codex":[0.9967157,0.001836972,0.0008209572,0.0003371889,0.00008392423,0.0002052969],"domain_scores_gemma":[0.9912358,0.00727221,0.0008228861,0.0002616188,0.0002902796,0.0001172136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001685503,0.0004600182,0.9340408,0.00005835944,0.0001820414,0.00009341779,0.0002069919,0.000665847,0.02350335,0.00003262548,0.000001458763,0.03906958],"study_design_scores_gemma":[0.003399719,0.02271079,0.9688219,0.00008956732,0.00008701435,0.0002101157,0.00009941664,0.00006385449,0.004340134,0.00007068554,0.00002133516,0.00008540738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972439,0.0009905985,0.0001482575,0.00002829208,0.0007722147,0.0003245859,0.00001828093,0.000006274017,0.000467628],"genre_scores_gemma":[0.9986429,0.0002107456,0.0008757412,0.00002049721,0.0001935823,9.950993e-7,0.00002082029,0.00001757028,0.00001716353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03898417,"threshold_uncertainty_score":0.9911752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08880043292593438,"score_gpt":0.3937274845702247,"score_spread":0.3049270516442903,"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."}}