{"id":"W2066816119","doi":"10.1115/detc2003/vib-48501","title":"Compliance Optimisation for Robotic Assembly","year":2003,"lang":"en","type":"article","venue":"","topic":"Robotic Mechanisms and Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Compliance (psychology); Robot; Decoupling (probability); Control theory (sociology); Workspace; Robot end effector; Stiffness; Engineering; Computer science; Control engineering; Artificial intelligence; Structural engineering; Control (management)","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":[0.0007163754,0.0006748578,0.0007406852,0.0006767887,0.0004538958,0.0005740572,0.0004005488,0.0007401578,0.002850448],"category_scores_gemma":[0.001727251,0.0004817831,0.0005231817,0.0006002414,0.0007611013,0.000596691,0.000912906,0.0006057378,0.0007101325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005564789,"about_ca_system_score_gemma":0.0005982832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008426696,"about_ca_topic_score_gemma":0.0007367093,"domain_scores_codex":[0.9995326,0.0001339148,0.00001977279,0.00005566037,0.0002199486,0.00003806859],"domain_scores_gemma":[0.9995552,0.0002441162,0.0000886799,0.00003504761,0.00006242255,0.00001459439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005214358,0.00005092266,0.0002423647,0.00021472,0.00002359363,0.00007647969,0.00005887526,0.8834736,0.01146778,0.02898102,0.001050045,0.07430837],"study_design_scores_gemma":[0.0000247048,0.00009905812,0.0003140258,0.00003203882,0.00001012627,0.00006639751,0.00002247237,0.9614999,0.002334851,0.03051942,0.005060369,0.00001666364],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01934011,0.001043661,0.9658991,0.0002183517,0.00003824547,0.00007052374,0.00003077644,0.0003463755,0.01301291],"genre_scores_gemma":[0.643994,0.001789844,0.3360044,0.0001361364,0.0001013257,0.0004965001,0.0001841292,0.0003966943,0.01689693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002850448,"threshold_uncertainty_score":0.00953567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03755260827510411,"score_gpt":0.2477985850414804,"score_spread":0.2102459767663764,"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."}}