{"id":"W3207472327","doi":"10.1109/icra48506.2021.9561791","title":"Automated End-Effector Alignment for Robotic Cell Manipulation","year":2021,"lang":"en","type":"article","venue":"","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Canadian Institute for Advanced Research","funders":"","keywords":"Robot end effector; Computer science; Effector; Robot; Artificial intelligence; Cell biology; Biology","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":[0.0002816076,0.0005619657,0.0004464141,0.0002796745,0.0002689568,0.0003272437,0.0008400272,0.0004129423,0.001175745],"category_scores_gemma":[0.0004706488,0.0002509237,0.000267338,0.0002846484,0.0002642318,0.0003912191,0.0004573582,0.0004733663,0.0006504286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003761582,"about_ca_system_score_gemma":0.0004974401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009467216,"about_ca_topic_score_gemma":0.001071363,"domain_scores_codex":[0.9994542,0.00005623361,0.0000276699,0.0001341597,0.0002918787,0.00003588285],"domain_scores_gemma":[0.9997593,0.00004545068,0.00007645721,0.00004004824,0.00006802969,0.00001070124],"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":[0.0001215031,0.00007730135,0.0006544992,0.000169098,0.00002075264,0.0001169805,0.00009774536,0.0564899,0.7406338,0.002583321,0.001019192,0.1980159],"study_design_scores_gemma":[0.00003615321,0.0005217541,0.00323435,0.00001942949,0.00003203861,0.000250773,0.00002650429,0.5011696,0.4780207,0.0009227439,0.01570154,0.00006449877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.036734,0.0003816599,0.9588805,0.00003853055,0.00004813568,0.0000680101,0.00003262121,0.001591905,0.002224731],"genre_scores_gemma":[0.5426441,0.000350843,0.4528704,0.00007116383,0.00002758628,0.0001633824,0.0001842834,0.0001063642,0.003581862],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001175745,"threshold_uncertainty_score":0.003933191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02601250541317196,"score_gpt":0.2883014331093979,"score_spread":0.262288927696226,"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."}}