{"id":"W4365142055","doi":"10.1007/s10514-023-10094-9","title":"DiSECt: a differentiable simulator for parameter inference and control in robotic cutting","year":2023,"lang":"en","type":"article","venue":"Autonomous Robots","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vector Institute; University of Toronto","funders":"Google","keywords":"Computer science; Slicing; Simulation; Controller (irrigation); Differentiable function; Solver; Stiffness; Robotics; Robot; Artificial intelligence; Computer graphics (images)","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":[0.000120207,0.0001502818,0.0002398569,0.0001669723,0.00006928935,0.00007415748,0.00007441607,0.00007376656,0.00002566346],"category_scores_gemma":[0.0001403613,0.0001566135,0.00004256399,0.0002096847,0.00001530871,0.0001295637,0.00002439417,0.0001372817,0.00004066151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004359972,"about_ca_system_score_gemma":0.00001200933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001734257,"about_ca_topic_score_gemma":0.00002615939,"domain_scores_codex":[0.9991127,0.00002163017,0.0002414951,0.0002021063,0.00006765466,0.0003543697],"domain_scores_gemma":[0.9992942,0.0004584289,0.00003027343,0.0001320137,0.00001559513,0.00006946034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004239303,0.000006481646,0.02655233,0.00006611475,0.00001630532,0.000002742356,0.0003033073,0.9700735,0.0006078968,0.0001530914,0.00003872629,0.002175268],"study_design_scores_gemma":[0.0007131772,0.00001899415,0.103443,0.00003626999,0.00001208254,8.765625e-7,0.00002463856,0.8950672,0.00003847466,0.0002843816,0.0001967482,0.0001641639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.629775,0.0001443018,0.3683169,0.0001026891,0.0002431789,0.0005364014,0.000001539517,0.0007185512,0.0001613887],"genre_scores_gemma":[0.9988474,0.000009651914,0.0006405491,0.00005775631,0.00004032161,0.00008041863,0.00001545391,0.00004085025,0.0002675842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3690724,"threshold_uncertainty_score":0.6386515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02060066404619508,"score_gpt":0.256513898686377,"score_spread":0.2359132346401819,"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."}}