{"id":"W3203250742","doi":"10.1016/j.fertnstert.2021.09.008","title":"Let the data do the talking: the need to consider mosaicism during embryo selection","year":2021,"lang":"en","type":"review","venue":"Fertility and Sterility","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"CReATe Fertility Centre; University of Toronto","funders":"National Institute of General Medical Sciences; National Institutes of Health; American Society for Reconstructive Microsurgery; Johns Hopkins University","keywords":"Aneuploidy; Hindsight bias; Selection (genetic algorithm); Embryo; Biology; Genetics; Psychology; Computer science; Chromosome; Gene; Artificial intelligence","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":[0.004733185,0.0004744389,0.001945733,0.001730627,0.0005143888,0.002402607,0.001456557,0.003571113,0.003957722],"category_scores_gemma":[0.01343405,0.0003147211,0.000826738,0.001202954,0.001516809,0.004061572,0.001169388,0.006605104,0.001319291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008605898,"about_ca_system_score_gemma":0.003241534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002744898,"about_ca_topic_score_gemma":0.00674645,"domain_scores_codex":[0.9983059,0.0007393517,0.0003187262,0.0001376318,0.0004268573,0.00007144857],"domain_scores_gemma":[0.9881913,0.009196244,0.000602242,0.0002195247,0.0015758,0.0002148169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001066952,0.00002406373,0.0006139826,0.01573703,0.0002718388,0.0005027052,0.0002253586,0.0001668138,0.00055207,0.008791331,0.1345176,0.8384904],"study_design_scores_gemma":[0.00003674625,0.00004479046,0.0007340509,0.01764671,0.0002569294,0.001453642,0.0002283149,0.0000591928,0.0001380713,0.007266882,0.9721003,0.00003441784],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005880684,0.9861942,0.0001526233,0.01160333,0.00129799,0.000003286388,0.00002036334,0.000005895685,0.0006634697],"genre_scores_gemma":[0.00141643,0.9844403,0.000733368,0.01048011,0.002219055,0.00000981103,0.00004821639,0.000008872982,0.0006437444],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004733185,"threshold_uncertainty_score":0.02503181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1172424573222606,"score_gpt":0.3689276978820224,"score_spread":0.2516852405597618,"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."}}