{"id":"W1669012000","doi":"10.1109/robot.1999.769938","title":"An integration of robot programming and sequence planning","year":2003,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Sequence (biology); Task (project management); Robot; Automatic programming; Inductive programming; Programming language; Software engineering; Artificial intelligence; Human–computer interaction; Programming paradigm; Engineering; Systems 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004332047,0.00003728817,0.00003949349,0.00002410713,0.00001417911,0.00001693047,0.00001720313,0.00001996224,0.00001323502],"category_scores_gemma":[0.000005688324,0.00003251188,0.00000390424,0.00003459136,0.000006665944,0.0001233801,0.000001249008,0.00002619499,2.075208e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000453849,"about_ca_system_score_gemma":0.000002302758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005953628,"about_ca_topic_score_gemma":0.000002276341,"domain_scores_codex":[0.9998078,0.000003860977,0.00006244962,0.00004653728,0.00002994513,0.00004940408],"domain_scores_gemma":[0.9999163,0.000004525566,0.000009281062,0.00004013186,0.00001213656,0.00001764365],"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":[0.000001248974,0.000007408511,0.001376475,0.00009075774,0.000004427496,5.268925e-7,0.0008313856,0.9301001,0.01079524,0.003260195,0.000004899631,0.05352734],"study_design_scores_gemma":[0.0001462225,0.000059295,0.001982661,0.00006106366,0.000007202015,0.00000607992,0.0004474178,0.630595,0.3657015,0.0003530579,0.0004767202,0.0001638247],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2350603,0.00009107405,0.7617165,0.000002237173,0.00002988669,0.0000496066,2.069681e-7,0.0001129624,0.002937231],"genre_scores_gemma":[0.9260489,0.000008807895,0.07390608,0.000003062946,0.000003653898,0.000002804087,0.000002725337,0.000004909485,0.00001900451],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6909887,"threshold_uncertainty_score":0.1325796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357540301852356,"score_gpt":0.2568996066198963,"score_spread":0.2333242036013727,"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."}}