{"id":"W4365128442","doi":"10.1109/tase.2023.3264556","title":"Automated Morphological Grading of Human Blastocysts From Multi-Focus Images","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Automation Science and Engineering","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"CReATe Fertility Centre; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Blastocyst; Grading (engineering); Computer science; Artificial intelligence; Convolutional neural network; Pattern recognition (psychology); Embryo; Biology; Embryogenesis; Cell 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":[],"consensus_categories":[],"category_scores_codex":[0.0002101589,0.0001148293,0.0001222042,0.0004018279,0.000193485,0.00006601044,0.0001503331,0.00005250865,0.000009452861],"category_scores_gemma":[0.000009370407,0.0001152788,0.00002735321,0.0009512191,0.0001067115,0.0003118554,0.000002448576,0.0001167967,0.00001608858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005063367,"about_ca_system_score_gemma":0.00001309601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001830108,"about_ca_topic_score_gemma":0.000001022808,"domain_scores_codex":[0.9992014,0.00000413173,0.0002046177,0.0001827683,0.0002109615,0.0001961085],"domain_scores_gemma":[0.9996655,0.0000408243,0.00002588099,0.0001482048,0.0000564147,0.00006319556],"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":[4.640776e-7,0.00001494727,0.000003195418,0.00002360173,0.000005329347,0.000001625646,0.000141432,0.1276734,0.8640909,0.00002410803,0.00007830053,0.007942773],"study_design_scores_gemma":[0.00008141714,0.000010283,0.001357365,0.00003279286,0.000004967986,0.000002907353,0.00001995803,0.6154664,0.3829039,0.00002876236,0.00001219691,0.00007912564],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4065729,0.00001188444,0.5893706,0.00002799352,0.0000803435,0.00008803118,0.00001836254,0.00378762,0.00004223701],"genre_scores_gemma":[0.9847561,0.00002317777,0.015119,0.000005203038,0.00000919516,0.00005650994,0.000002523336,0.00001679562,0.00001145867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5781832,"threshold_uncertainty_score":0.4700933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02324413326760491,"score_gpt":0.2815626185474406,"score_spread":0.2583184852798357,"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."}}