{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005960336,0.001649228,0.001378382,0.001067101,0.0004871615,0.001180375,0.003189945,0.001099229,0.005566263],"category_scores_gemma":[0.002528936,0.0009692776,0.001441023,0.0009836545,0.0006182686,0.002559711,0.001890835,0.002170276,0.0026863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118467,"about_ca_system_score_gemma":0.001226454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02632309,"about_ca_topic_score_gemma":0.04612228,"domain_scores_codex":[0.999512,0.00005297271,0.0000202349,0.0002164745,0.0001266145,0.0000716943],"domain_scores_gemma":[0.9993073,0.0002321171,0.00006799829,0.0001944192,0.0001272563,0.00007096995],"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":[0.0005655379,0.0004311819,0.007292249,0.0002449436,0.0001974577,0.0001362586,0.0002210653,0.5027621,0.008981415,0.006563857,0.03391707,0.4386869],"study_design_scores_gemma":[0.0000104169,0.0000164598,0.0004582048,0.00001172434,0.000005304536,0.00002136717,0.00001771191,0.9928139,0.001247973,0.003333514,0.002050973,0.00001240218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02744088,0.0006954149,0.9294652,0.0003527574,0.0002614457,0.0001372793,0.004605892,0.03376939,0.003271708],"genre_scores_gemma":[0.5181456,0.0005325626,0.4509765,0.000565889,0.0002452809,0.0003646904,0.01933686,0.002649362,0.007183194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02632309,"threshold_uncertainty_score":0.05233973,"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."}}