{"id":"W4385452913","doi":"10.1109/tits.2023.3297068","title":"Spatio-Temporal Lattice Planning Using Optimal Motion Primitives","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Notation; Lattice (music); Integer lattice; Algorithm; Set (abstract data type); Mathematics; Discrete mathematics; Combinatorics; Computer science; Theoretical computer science; Artificial intelligence; Programming language; Arithmetic","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005238689,0.0003096877,0.0003197692,0.0006641042,0.0003824651,0.000212232,0.0004505999,0.0001623307,0.0000139456],"category_scores_gemma":[0.000005389319,0.000330497,0.0001653219,0.001308324,0.0000511194,0.000782317,8.359017e-7,0.0003114084,0.0002440997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001449998,"about_ca_system_score_gemma":0.00009216663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002144529,"about_ca_topic_score_gemma":0.000006889788,"domain_scores_codex":[0.9972622,0.0001602178,0.0007648878,0.0006442365,0.0007068932,0.00046156],"domain_scores_gemma":[0.9987382,0.0002187977,0.0002353418,0.0004488159,0.0001883691,0.0001704589],"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":[0.00002127863,0.00007575114,0.0004897959,0.00006454779,0.00006423863,0.00007438081,0.004557913,0.9906231,0.00031096,0.000497462,0.00003041006,0.003190195],"study_design_scores_gemma":[0.0002837873,0.000114294,0.002064852,0.0002903536,0.00004439731,0.00002561977,0.001084496,0.986673,0.008756401,0.00002777828,0.000264076,0.0003709615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1046139,0.00004158131,0.8907915,0.00006468893,0.002899605,0.0004819834,0.0000576177,0.000987715,0.00006142216],"genre_scores_gemma":[0.9642606,0.00001482755,0.03508776,0.00003145956,0.00008667405,0.00008606276,0.00007533113,0.0000391315,0.0003180978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8596467,"threshold_uncertainty_score":0.9999147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07830150321909707,"score_gpt":0.31075451657102,"score_spread":0.232453013351923,"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."}}