{"id":"W4327740064","doi":"10.3390/math11061449","title":"Optimal Robot Pose Estimation Using Scan Matching by Turning Function","year":2023,"lang":"en","type":"article","venue":"Mathematics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West","funders":"","keywords":"Histogram; Computer science; Orientation (vector space); Artificial intelligence; Robot; Pose; Mobile robot; Computer vision; Matching (statistics); Position (finance); Function (biology); Similarity (geometry); Algorithm; Mathematics; Image (mathematics)","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":[0.0001708129,0.0001375417,0.0001439684,0.000118198,0.000112822,0.00009333219,0.00006318948,0.00006206465,0.0000282128],"category_scores_gemma":[0.00003206289,0.0001455485,0.00003824391,0.0003234434,0.00001099101,0.0001399786,0.00001858558,0.0001010996,0.00009494895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007803497,"about_ca_system_score_gemma":0.000007951277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000708094,"about_ca_topic_score_gemma":8.363922e-7,"domain_scores_codex":[0.9992165,0.00001189859,0.0002600746,0.0001086039,0.0001895006,0.000213405],"domain_scores_gemma":[0.9996661,0.00005462492,0.0000498716,0.0001502087,0.00002912782,0.00005007085],"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":[0.000001060583,0.00001073692,0.00001124578,0.0001521109,0.00001598333,0.000002146663,0.0005189858,0.9686933,0.02872716,0.0004125573,0.0007748599,0.0006798376],"study_design_scores_gemma":[0.0001137853,0.00001256366,0.00002800105,0.0000867529,0.00003104147,0.000007130483,0.0002728008,0.9954898,0.002523459,0.001226769,0.00005054063,0.0001573138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3735251,0.00002178432,0.6254392,0.00001271723,0.0002147643,0.00007843578,0.000003359889,0.0004487812,0.0002557828],"genre_scores_gemma":[0.8993593,0.00001266718,0.1001682,0.0000188739,0.00008241191,0.000003484111,0.0001253237,0.00008373916,0.0001460132],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5258341,"threshold_uncertainty_score":0.5935296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675516895129174,"score_gpt":0.2320125410522408,"score_spread":0.2152573721009491,"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."}}