{"id":"W3092872945","doi":"10.1109/tbme.2020.3031043","title":"Automated Embryo Manipulation and Rotation via Robotic nDEP-Tweezers","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Micromanipulator; Dielectrophoresis; Computer science; Tweezers; Embryo; Artificial intelligence; Rotation (mathematics); Computer vision; Engineering; Nanotechnology; Materials science; Biology; Electrical engineering; Cell biology; Microfluidics","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":[0.0003128755,0.0003705697,0.0002354744,0.0002107526,0.0002774492,0.0002555294,0.0006690472,0.0003334075,0.0009413398],"category_scores_gemma":[0.0005481688,0.0003224891,0.0002167167,0.000117084,0.0002899485,0.0004116362,0.0005816893,0.0003292745,0.0004793014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002604652,"about_ca_system_score_gemma":0.0003715645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006997552,"about_ca_topic_score_gemma":0.001270379,"domain_scores_codex":[0.9996673,0.00002712042,0.00002154559,0.00008534035,0.0001708889,0.00002776775],"domain_scores_gemma":[0.9997839,0.00008046576,0.00004766012,0.00003993892,0.00003721059,0.00001079058],"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":[0.00004294918,0.00001622091,0.0003073273,0.00007046793,0.000004696923,0.0000723803,0.0000310441,0.00152761,0.9727313,0.0004973977,0.0003125343,0.02438609],"study_design_scores_gemma":[0.0000273802,0.000139523,0.00189148,0.00001045432,0.00001335233,0.0002767078,0.00001657839,0.03633692,0.9512839,0.0002532333,0.009716878,0.00003358752],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3120505,0.001409247,0.6768439,0.0004069485,0.0001655299,0.0003815745,0.0003767442,0.002247441,0.006118116],"genre_scores_gemma":[0.4726021,0.001135896,0.5171083,0.0001507353,0.00004270484,0.0004449208,0.000248291,0.00007000077,0.008197051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009413398,"threshold_uncertainty_score":0.003149092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280349826371902,"score_gpt":0.2005451940509261,"score_spread":0.187741695787207,"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."}}