{"id":"W3201213425","doi":"10.36227/techrxiv.16553580.v1","title":"LiCaNet: Further Enhancement of Joint Perception and Motion Prediction based on Multi-Modal Fusion","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Artificial intelligence; Computer science; Computer vision; Perception; Motion (physics); Fusion; Sensor fusion; Pipeline (software); Displacement (psychology); Image fusion; Modal; Reliability (semiconductor); Lidar; Image (mathematics); Geography; Remote sensing; Psychology","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":[0.0001716777,0.0002298593,0.0002447417,0.0001354229,0.0000796366,0.00006611727,0.0002706289,0.000180084,0.00009393918],"category_scores_gemma":[0.00001453271,0.0002171228,0.0000860122,0.0001850989,0.00004768806,0.0001476851,0.0005776132,0.000309218,0.000007404962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001294175,"about_ca_system_score_gemma":0.00005311767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004757564,"about_ca_topic_score_gemma":0.00001977617,"domain_scores_codex":[0.9981543,0.00009642669,0.000397431,0.0008233991,0.0003572879,0.0001711275],"domain_scores_gemma":[0.9985742,0.00003979167,0.0002636536,0.0008895242,0.0001534179,0.00007942977],"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":[0.00004785035,0.001467961,0.0009775583,0.0003465608,0.00004433143,0.000004272626,0.001943311,0.2292754,0.3351993,0.001720378,0.0002840982,0.428689],"study_design_scores_gemma":[0.0003169651,0.0001235138,0.02730839,0.0001563897,0.00001200096,0.000001940793,0.00004341869,0.9585487,0.01294661,0.0003025747,0.0000605407,0.0001790036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1057221,0.00003353599,0.8919879,0.0009649568,0.0002622964,0.0006352206,0.000008877047,0.000135972,0.0002492023],"genre_scores_gemma":[0.808899,0.0001395947,0.1903216,0.0002042091,0.00006772232,0.0001462509,0.00009653311,0.00001301923,0.0001121076],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7292733,"threshold_uncertainty_score":0.8854009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03004112626537556,"score_gpt":0.2682871843364028,"score_spread":0.2382460580710272,"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."}}