{"id":"W4390189964","doi":"10.1109/iccvw60793.2023.00486","title":"DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport","year":2023,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"CODE; Ministry of Education","keywords":"Odometry; Lidar; Computer science; Artificial intelligence; Remote sensing; Computer vision; Geology; Mobile robot; Robot","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000979144,0.0001158979,0.0001279098,0.0001556182,0.00006164428,0.00003278042,0.00007499517,0.00008254765,0.0002629354],"category_scores_gemma":[0.0000124651,0.0001202027,0.00007052497,0.0005140948,0.00001597609,0.0001183588,0.000008721251,0.00007708985,0.0001356725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003250131,"about_ca_system_score_gemma":0.00001228683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003160586,"about_ca_topic_score_gemma":0.00001438134,"domain_scores_codex":[0.999188,0.00001009766,0.0002168739,0.0001367571,0.0001835085,0.0002647496],"domain_scores_gemma":[0.9997276,0.00002516312,0.00001191808,0.0001289297,0.00002717993,0.00007918497],"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":[0.000005000169,0.000005082393,0.0007655151,0.00002775744,0.00002303626,0.00003493427,0.0001080149,0.9939045,0.004272153,0.0001931007,0.0001423627,0.000518539],"study_design_scores_gemma":[0.0001907469,0.00001274139,0.000778057,0.00001129988,0.00002758726,0.000004898331,0.00007766753,0.9911907,0.006962974,0.00001285354,0.000570207,0.0001603082],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4892997,0.00002905752,0.5094867,0.00001262424,0.0003533432,0.00005270373,0.000001969119,0.0004119022,0.0003520222],"genre_scores_gemma":[0.9953269,0.00003517159,0.004223437,0.00002288431,0.0002034568,0.000002278939,0.00003974351,0.00004284622,0.0001033008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5060272,"threshold_uncertainty_score":0.4901722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02408488043965996,"score_gpt":0.2452121686723089,"score_spread":0.221127288232649,"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."}}