{"id":"W2539697279","doi":"10.1002/rob.21669","title":"Expanding the Limits of Vision‐based Localization for Long‐term Route‐following Autonomy","year":2016,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robustness (evolution); Computer science; Computer vision; Artificial intelligence; Robot; Field of view; Stereo cameras; Metric (unit); Real-time computing; Stereo camera; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002366482,0.00009964279,0.0001969871,0.0001103601,0.00006160377,0.00003006502,0.00015001,0.00009339304,0.00001173986],"category_scores_gemma":[0.0001528001,0.00005893755,0.0001785824,0.0001177922,0.00001511503,0.0001406845,0.000007664359,0.00008259802,7.419789e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006709886,"about_ca_system_score_gemma":0.00005694295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.680704e-7,"about_ca_topic_score_gemma":0.00000271718,"domain_scores_codex":[0.9991285,0.00002120898,0.0004704545,0.00005914796,0.0001807826,0.0001399657],"domain_scores_gemma":[0.9990416,0.0004354148,0.0001788171,0.0001407737,0.0001524143,0.00005105247],"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":[0.00002010601,0.00002190147,0.006117959,0.00005864477,0.00005492357,0.000004352861,0.00009028811,0.9819173,0.003989569,0.0003613238,0.0005130238,0.006850604],"study_design_scores_gemma":[0.002851115,0.0007169782,0.005609896,0.001373579,0.0002940521,0.00001738549,0.00007563973,0.8838286,0.1033735,0.0006075846,0.0008795296,0.0003721599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01582601,0.0001370749,0.9819781,0.001045842,0.0007930913,0.0001107294,0.000001507444,0.00001653511,0.0000911248],"genre_scores_gemma":[0.9923953,0.0000491915,0.00717345,0.0001373412,0.0001786748,0.000001089858,0.000001821704,0.00002145681,0.00004163066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9765694,"threshold_uncertainty_score":0.2403404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02078084904549751,"score_gpt":0.2729347053296254,"score_spread":0.252153856284128,"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."}}