{"id":"W3213044144","doi":"10.48550/arxiv.2111.07971","title":"Towards Optimal Strategies for Training Self-Driving Perception Models in Simulation","year":2021,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Exploit; Perception; Domain (mathematical analysis); Artificial intelligence; Human–computer interaction; Focus (optics); Segmentation; Adaptation (eye); Machine learning; Driving simulator; Computer security","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":[0.001643726,0.001278822,0.001099129,0.0006558651,0.0004042261,0.0009272246,0.002368535,0.001787694,0.001654297],"category_scores_gemma":[0.006474163,0.001009124,0.0008776752,0.0004520314,0.001187005,0.00215624,0.001630149,0.00274311,0.0005038936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001256266,"about_ca_system_score_gemma":0.001232128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006747185,"about_ca_topic_score_gemma":0.006664827,"domain_scores_codex":[0.9995618,0.0001865337,0.00001970376,0.000135106,0.00003519274,0.00006169083],"domain_scores_gemma":[0.99748,0.001816597,0.0001538588,0.0001922542,0.0002276056,0.0001297155],"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":[0.0001077311,0.0001366239,0.001225908,0.0000690286,0.00005923476,0.00003219402,0.0001108607,0.9330606,0.002421022,0.003825661,0.001261544,0.05768951],"study_design_scores_gemma":[0.000005588217,0.00001545149,0.00006396577,0.000004448802,0.000003177757,0.000003607174,0.00001003575,0.9967668,0.0003327232,0.002712984,0.00007873906,0.000002574489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1138659,0.0006102904,0.8814035,0.0007626434,0.00005801968,0.00009848212,0.0001473288,0.001387053,0.001666872],"genre_scores_gemma":[0.8653823,0.0002232183,0.1309884,0.0005228177,0.00005318393,0.0002072565,0.0005778442,0.0002067949,0.001838274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006747185,"threshold_uncertainty_score":0.01341581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.130858352525539,"score_gpt":0.2278842024047157,"score_spread":0.0970258498791767,"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."}}