{"id":"W4312868755","doi":"10.1109/tmech.2022.3220181","title":"Robotic Blastocyst Biopsy","year":2022,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"University of Toronto; Canada Research Chairs","keywords":"Biopsy; Blastocyst; Computer science; Artificial intelligence; Biomedical engineering; Algorithm; Biology; Embryo; Pathology; Engineering; Cell biology; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004150338,0.0005606033,0.0004761107,0.0005417714,0.0003330221,0.0005568489,0.0007313284,0.0007847276,0.005056322],"category_scores_gemma":[0.0005941395,0.0003741051,0.0004649801,0.0001802877,0.0002635708,0.0004197107,0.0006346261,0.0004892041,0.001807904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003868442,"about_ca_system_score_gemma":0.000622871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001219514,"about_ca_topic_score_gemma":0.00169479,"domain_scores_codex":[0.9995404,0.00004585258,0.00002575536,0.0001413097,0.0002169879,0.00002975373],"domain_scores_gemma":[0.999774,0.00006708797,0.00003921052,0.00005141028,0.00004046175,0.00002782156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002866779,0.00009574416,0.002489439,0.0006493114,0.00006556365,0.001197849,0.0001320784,0.006077664,0.6608179,0.003611461,0.00685734,0.317719],"study_design_scores_gemma":[0.0001672588,0.001462453,0.02320537,0.0002035611,0.000232985,0.01633636,0.0001263246,0.1145468,0.6472852,0.00247273,0.1937293,0.000231711],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1226009,0.007688631,0.8286411,0.0006361762,0.0007044502,0.00069388,0.0009317828,0.00741119,0.03069191],"genre_scores_gemma":[0.4128231,0.004037007,0.5588135,0.0008424873,0.0002173073,0.0005021102,0.001283967,0.0002456977,0.02123482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005056322,"threshold_uncertainty_score":0.01691508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01556684379043261,"score_gpt":0.2495095190722573,"score_spread":0.2339426752818247,"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."}}