{"id":"W4286543002","doi":"10.1109/lra.2022.3192885","title":"Are We Ready for Radar to Replace Lidar in All-Weather Mapping and Localization?","year":2022,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lidar; Radar; Backup; Remote sensing; Weather radar; Meteorology; 3D radar; Computer science; Environmental science; Radar imaging; Radar engineering details; Geography; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005432959,0.001141649,0.0009813397,0.000643397,0.0008027255,0.002310328,0.002106532,0.001993463,0.008362613],"category_scores_gemma":[0.01317795,0.0005947489,0.000656128,0.001044194,0.0009761815,0.01002427,0.001554054,0.001914218,0.009110709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004244484,"about_ca_system_score_gemma":0.001136508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005479015,"about_ca_topic_score_gemma":0.01100071,"domain_scores_codex":[0.998257,0.0005315825,0.0001014916,0.0003913984,0.00032658,0.0003920002],"domain_scores_gemma":[0.9950546,0.001290038,0.0004214417,0.001287228,0.001641894,0.0003047117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001472581,0.0002209233,0.03217809,0.00160183,0.0003453518,0.0004882667,0.0005386512,0.02034735,0.03659958,0.0149638,0.05691193,0.8343316],"study_design_scores_gemma":[0.0007795412,0.002946919,0.06508955,0.002517503,0.000779617,0.003936463,0.007608708,0.1704225,0.1033826,0.07925729,0.5626234,0.0006559],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.1742037,0.0256713,0.7095587,0.04442609,0.006148022,0.0002065027,0.003832256,0.01381952,0.02213393],"genre_scores_gemma":[0.6412863,0.005554667,0.3336058,0.00723054,0.0006197745,0.0001014966,0.003317486,0.001814866,0.006469029],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.008362613,"threshold_uncertainty_score":0.0287326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03119363341485665,"score_gpt":0.246496627868059,"score_spread":0.2153029944532023,"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."}}