{"id":"W1501911729","doi":"10.1109/iecon.1994.397888","title":"Robot path planning using neural networks and fuzzy logic","year":2002,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Trajectory; Motion planning; Fuzzy logic; Object (grammar); Computer science; Robot; Path (computing); Artificial neural network; Artificial intelligence; Control engineering; Computer vision; 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":[0.0001205006,0.0001106075,0.0001485543,0.00003246655,0.0001361714,0.0001871348,0.0002857536,0.00005666852,0.000008016191],"category_scores_gemma":[0.000007382168,0.0000821756,0.00003179488,0.0001434472,0.00002451937,0.0002647948,0.0001393823,0.0000951728,0.000007944106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001268541,"about_ca_system_score_gemma":0.00000275114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003955774,"about_ca_topic_score_gemma":7.331544e-7,"domain_scores_codex":[0.9991273,0.00004955145,0.0001514,0.0002718686,0.0001195899,0.0002802997],"domain_scores_gemma":[0.999573,0.00004684681,0.00004946064,0.0002268848,0.00001869907,0.00008508825],"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":[0.000009158933,0.00008726132,0.01774616,0.00002487878,0.00004543759,0.0003865324,0.0009774001,0.6452746,0.0005599894,0.2288156,0.003577281,0.1024957],"study_design_scores_gemma":[0.0002002406,0.0000443658,0.0013198,0.000008507152,0.00000264733,0.00008534169,0.0000255245,0.9962029,0.000001108948,0.001893793,0.00009602333,0.0001197311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02215184,0.003895312,0.920697,0.0005620224,0.0005608877,0.0001497248,1.820163e-7,0.0002739934,0.051709],"genre_scores_gemma":[0.9914194,0.000008164153,0.007301287,0.0008479186,0.0001513218,0.000002715514,1.725187e-7,0.000004208586,0.0002647844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9692676,"threshold_uncertainty_score":0.3351024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0509725590017716,"score_gpt":0.2362826599469374,"score_spread":0.1853101009451658,"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."}}