{"id":"W4251175326","doi":"10.1007/978-0-387-22458-9_5","title":"Trajectory Planning: Pick-and-Place Operations","year":2007,"lang":"en","type":"book-chapter","venue":"Mechanical engineering series","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Process (computing); Robot; Trajectory; Ideal (ethics); Object (grammar); Motion (physics); Simple (philosophy); Terrain; Artificial intelligence; Control engineering; Simulation; Engineering","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":[0.0002209701,0.001868218,0.000894969,0.00074745,0.0006865812,0.002348134,0.001627626,0.001162358,0.02006113],"category_scores_gemma":[0.0005362524,0.0009283481,0.0006869762,0.003150455,0.001133776,0.002333581,0.001074264,0.001900579,0.008201559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00135229,"about_ca_system_score_gemma":0.002116956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01110422,"about_ca_topic_score_gemma":0.01508924,"domain_scores_codex":[0.9997659,0.00002760951,0.00001262114,0.00006256756,0.0001109679,0.00002027431],"domain_scores_gemma":[0.9998988,0.00003194914,0.000007071768,0.00002130918,0.00003173221,0.000009164666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002834184,0.00004273902,0.0001167027,0.0003730732,0.0000170622,0.00006391057,0.000177099,0.1070222,0.001851577,0.2289467,0.08946758,0.5718929],"study_design_scores_gemma":[0.00001165798,0.00003798505,0.0002684623,0.0002910028,0.00002474795,0.0002147333,0.000164188,0.1429576,0.003373035,0.2536208,0.598989,0.00004684698],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00090789,0.007820656,0.885112,0.0006158606,0.0006219696,0.0000636283,0.0003860306,0.001449183,0.1030228],"genre_scores_gemma":[0.04797315,0.0380546,0.6651063,0.0003270252,0.0005497112,0.0002976819,0.002203542,0.001398524,0.2440895],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02006113,"threshold_uncertainty_score":0.06711119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02119167356402826,"score_gpt":0.2251884907045103,"score_spread":0.203996817140482,"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."}}