{"id":"W2886517076","doi":"10.1016/j.compbiomed.2018.08.001","title":"A hybrid approach for multiple blastomeres identification in early human embryo images","year":2018,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Hemophilia Society; Pacific Centre for Reproductive Medicine; Simon Fraser University","funders":"","keywords":"Embryo; Blastomere; Identification (biology); Artificial intelligence; Computational biology; Computer science; Biology; Pattern recognition (psychology); Genetics; Embryogenesis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003159566,0.00009372395,0.0002534215,0.0001957225,0.00005344576,0.000003602023,0.00007159847,0.00007301576,0.000002859299],"category_scores_gemma":[0.0004062456,0.00007226669,0.00001688588,0.00008869518,0.0004810288,0.00002806092,0.00004178029,0.0001147734,0.000001548949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001736496,"about_ca_system_score_gemma":0.00001142373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002012545,"about_ca_topic_score_gemma":0.00002317342,"domain_scores_codex":[0.9992493,0.00003765428,0.0002335996,0.0002577873,0.00004085984,0.0001808112],"domain_scores_gemma":[0.999404,0.0002943639,0.00005196366,0.0001376848,0.00004526061,0.00006670201],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007133652,0.0003175694,0.9088619,0.0002106374,0.00005325113,0.00002918864,0.00143341,0.000005783879,0.03503992,0.003063819,0.007291292,0.04297991],"study_design_scores_gemma":[0.005683575,0.001622228,0.98093,0.0002909062,0.00003071624,0.00004362256,0.00009383557,0.006218871,0.002597343,0.00192014,0.0004491374,0.0001196337],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9328952,0.0005510629,0.0649849,0.0004923262,0.0002225617,0.0003717304,0.000008021755,0.00003085357,0.0004433701],"genre_scores_gemma":[0.9922925,0.00004121197,0.006678829,0.0003579098,0.0003805634,0.00003105885,0.0001571623,0.000006590447,0.00005413718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07206814,"threshold_uncertainty_score":0.294695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02743682406719625,"score_gpt":0.3323174029096563,"score_spread":0.3048805788424601,"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."}}