{"id":"W4292673968","doi":"10.1155/2022/4075910","title":"A Variable Radius Side Window Direct SLAM Method Based on Semantic Information","year":2022,"lang":"en","type":"article","venue":"Computational Intelligence and Neuroscience","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Computer science; Robustness (evolution); Artificial intelligence; Simultaneous localization and mapping; Computer vision; Preprocessor; RGB color model; Feature extraction; Feature (linguistics); Pixel; Mobile robot; Pattern recognition (psychology); Robot","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":[0.0002214451,0.0001003251,0.00009202572,0.000170605,0.0002963406,0.00009284165,0.0001364669,0.00001694293,0.0000248095],"category_scores_gemma":[0.00008464078,0.0001060304,0.00002194723,0.0005543802,0.00004078745,0.0002285721,0.00003187529,0.0001258718,0.000007537874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004022474,"about_ca_system_score_gemma":0.00003615689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008227514,"about_ca_topic_score_gemma":3.05096e-7,"domain_scores_codex":[0.9990935,0.00005841159,0.0001963769,0.0001647467,0.0003346346,0.0001523154],"domain_scores_gemma":[0.9995166,0.0002514381,0.00003677333,0.00009469641,0.00004479333,0.00005567483],"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":[0.000006227456,0.00001636045,0.00004344663,0.00001515858,9.055421e-7,0.00000260514,0.00007470704,0.9893537,0.000404508,0.006215491,0.00008815369,0.003778759],"study_design_scores_gemma":[0.00005524004,0.0001039749,0.000539362,0.000008146143,0.000003788856,0.00001286347,0.00002578041,0.9934251,0.001673829,0.002329589,0.001705621,0.0001166831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002097745,0.00001891158,0.9955389,0.0001124766,0.0003916553,0.0001283213,0.00001514281,0.00009731033,0.001599545],"genre_scores_gemma":[0.9859074,0.000007988437,0.01250391,0.001492954,0.00001375202,0.00001638735,0.00002483179,0.000008258103,0.00002455427],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9838096,"threshold_uncertainty_score":0.4323792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02021648305384566,"score_gpt":0.247897347525345,"score_spread":0.2276808644714993,"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."}}