{"id":"W3160238730","doi":"10.1038/s41585-021-00465-1","title":"Machine learning for sperm selection","year":2021,"lang":"en","type":"review","venue":"Nature Reviews Urology","topic":"Reproductive Biology and Fertility","field":"Medicine","cited_by":97,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Selection (genetic algorithm); Sperm Retrieval; Sperm; Artificial intelligence; Machine learning; Andrology; Male infertility; Infertility; Pregnancy; Genetics; Computer science","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":[0.001075464,0.001266667,0.002014976,0.001500626,0.000265577,0.001373795,0.001087344,0.0020089,0.008028679],"category_scores_gemma":[0.002541341,0.0003777712,0.0007494843,0.001777922,0.001036823,0.00196578,0.001034321,0.003576763,0.003138776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000954012,"about_ca_system_score_gemma":0.001393439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001396616,"about_ca_topic_score_gemma":0.001807071,"domain_scores_codex":[0.999686,0.0000909334,0.00002722308,0.00006960971,0.00009910571,0.00002717942],"domain_scores_gemma":[0.9991611,0.0005714842,0.00006999416,0.00003107033,0.000122349,0.00004400626],"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":[0.00005828819,0.00005576946,0.0001104488,0.006707069,0.0001427351,0.000070537,0.00001799797,0.001663446,0.0004647076,0.009145353,0.05965104,0.9219126],"study_design_scores_gemma":[0.0001027597,0.0001839294,0.001068348,0.006874182,0.000269232,0.0006841422,0.00003159371,0.002579008,0.0006970651,0.04052302,0.9469149,0.00007184529],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006877216,0.9958683,0.001132134,0.001075665,0.0006359916,0.000004900521,0.00003406064,0.00002309516,0.001157169],"genre_scores_gemma":[0.001975508,0.9918063,0.001289581,0.001126974,0.001890053,0.00001373705,0.00008850572,0.00001181204,0.001797629],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.008028679,"threshold_uncertainty_score":0.02685863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05692645138005442,"score_gpt":0.4000260246444141,"score_spread":0.3430995732643596,"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."}}