{"id":"W4402754114","doi":"10.1109/cvpr52733.2024.01373","title":"UnO: Unsupervised Occupancy Fields for Perception and Forecasting","year":2024,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Occupancy; Computer science; Perception; Artificial intelligence; Statistics; Psychology; Mathematics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007550793,0.00004261245,0.00003649435,0.00001107298,0.00008245138,0.00004456113,0.00002732973,0.00003044417,0.0004761685],"category_scores_gemma":[0.0000105966,0.00003436946,0.00002261975,0.00006711095,0.00002891809,0.00006021382,0.00002122415,0.00003420618,0.0001298653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001853141,"about_ca_system_score_gemma":0.000002327613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001466957,"about_ca_topic_score_gemma":0.00006182065,"domain_scores_codex":[0.9996442,0.000004753079,0.00006646044,0.0001537257,0.00004655304,0.00008428992],"domain_scores_gemma":[0.9998398,0.00005383554,0.000005155306,0.00007016887,0.000002082233,0.00002895397],"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":[0.000004810832,0.00001013901,0.002111153,0.00003136265,0.000005231549,6.578013e-7,0.000656736,0.00009431023,0.01741408,0.0007328792,0.01312244,0.9658162],"study_design_scores_gemma":[0.0002653273,0.00009106789,0.06094745,0.0000444067,0.00002873287,0.00003445826,0.0005678347,0.7695763,0.0009497994,0.007838818,0.1593547,0.0003011095],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8224741,0.00004263095,0.1014853,0.001218764,0.00008743937,0.0002257446,0.000003169396,0.0001326286,0.07433026],"genre_scores_gemma":[0.9793698,0.00000870522,0.01572718,0.0001380926,0.00004187167,0.000003703617,0.000004874204,0.000005896438,0.004699851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9655151,"threshold_uncertainty_score":0.5213711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02626284804892914,"score_gpt":0.2588033405801868,"score_spread":0.2325404925312576,"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."}}