{"id":"W4361282857","doi":"10.18280/jesa.560101","title":"Outdoor Localization for a Mobile Robot under Different Weather Conditions Using a Deep Learning Algorithm","year":2023,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Deep learning; Computer science; Mobile robot; Robot","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000226478,0.0006119445,0.0004080933,0.0003525453,0.0003385912,0.0004396554,0.000529726,0.0007793858,0.001140593],"category_scores_gemma":[0.0005523489,0.0002282941,0.0004825127,0.0003848258,0.0002201852,0.0005210236,0.0005701274,0.0005902911,0.000309737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004762357,"about_ca_system_score_gemma":0.0006088707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01074714,"about_ca_topic_score_gemma":0.00928882,"domain_scores_codex":[0.9998733,0.00001461916,0.000006645157,0.00005161879,0.00002317115,0.00003066899],"domain_scores_gemma":[0.9998868,0.00003056458,0.00001603588,0.00001174942,0.00004677716,0.00000807892],"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":[0.0001618915,0.0001081618,0.003202682,0.00006018003,0.00006466542,0.0001156276,0.00007522411,0.6729068,0.01116967,0.001052191,0.001246247,0.3098366],"study_design_scores_gemma":[0.000003325308,0.00002453242,0.0003877332,0.000003179929,0.000005239673,0.00001307632,0.00001012879,0.997744,0.001280057,0.000355166,0.0001705345,0.000003174069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1176611,0.0003289518,0.8774155,0.00020178,0.00006735799,0.00003628642,0.00009779104,0.001568852,0.002622406],"genre_scores_gemma":[0.8725803,0.0001553135,0.1227029,0.00009468065,0.0000273448,0.00007060394,0.0002709194,0.00004158088,0.004056211],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01074714,"threshold_uncertainty_score":0.02136916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02284119838699975,"score_gpt":0.2652583527363745,"score_spread":0.2424171543493747,"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."}}