{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004237654,0.001262337,0.001503927,0.001028911,0.0004777607,0.0008218533,0.001417568,0.0006597834,0.002410161],"category_scores_gemma":[0.001284087,0.0006794077,0.0009966651,0.001161031,0.0004931189,0.001591311,0.001828704,0.001349378,0.001099751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002887215,"about_ca_system_score_gemma":0.001556089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003613776,"about_ca_topic_score_gemma":0.005809636,"domain_scores_codex":[0.9992232,0.00006664321,0.00003682691,0.0002267139,0.0003771169,0.00006941352],"domain_scores_gemma":[0.9995585,0.00006053938,0.00005314769,0.0001170552,0.0001768524,0.0000338572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002145417,0.0001123613,0.0007468955,0.0002402157,0.0001170524,0.0001156979,0.0001491764,0.04552677,0.06668488,0.004404898,0.005171185,0.8765164],"study_design_scores_gemma":[0.00008355359,0.0002435318,0.001534092,0.00002999193,0.00005821127,0.0004507763,0.0001117048,0.9565455,0.02846117,0.004187135,0.008236235,0.00005802332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006399409,0.0001694522,0.9916607,0.00004904723,0.00007230325,0.00004774475,0.00005680974,0.0008421746,0.0007024268],"genre_scores_gemma":[0.168645,0.0004944864,0.8249131,0.0001395175,0.00011539,0.0002112631,0.0006269084,0.000260954,0.00459347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003613776,"threshold_uncertainty_score":0.00806284,"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."}}