{"id":"W3118576105","doi":"10.1109/iv47402.2020.9304776","title":"PSDet: Efficient and Universal Parking Slot Detection","year":2020,"lang":"en","type":"article","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Benchmark (surveying); Computer science; Generalization; Parking lot; Architecture; Artificial intelligence; State (computer science); Real-time computing; Machine learning; Data mining; Algorithm; 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":[0.00007068407,0.00006029091,0.00006749506,0.00004249908,0.0000378494,0.00003036692,0.00004746634,0.00003174819,0.00003685566],"category_scores_gemma":[0.00001812951,0.0000596423,0.00001399049,0.0001465421,0.00001301018,0.00002831383,0.00002692024,0.00008998311,0.00006818454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003831319,"about_ca_system_score_gemma":0.000004109012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002597625,"about_ca_topic_score_gemma":0.00001331059,"domain_scores_codex":[0.9995436,0.00001585842,0.00007186594,0.0001081468,0.0001191548,0.0001413417],"domain_scores_gemma":[0.9998034,0.00003052337,0.000005213303,0.00006184515,0.0000118818,0.00008709438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006301801,0.0000218187,0.005918551,0.000670006,0.0001611064,0.00007486053,0.004641072,0.2055848,0.7088866,0.001030729,0.003756042,0.06919135],"study_design_scores_gemma":[0.0002324275,0.00003436396,0.001991012,0.00001047783,0.000003503663,0.000007599033,0.0001942394,0.9261614,0.03870599,0.000001870899,0.0325447,0.0001124224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358562,0.0001319519,0.04490484,0.0001366667,0.0001974595,0.0001286479,7.983338e-7,0.0005425353,0.0181009],"genre_scores_gemma":[0.9996837,0.000005510252,0.0001060118,0.00002453911,0.0001013905,0.000002933328,3.224336e-7,0.00001565271,0.00005990317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7205766,"threshold_uncertainty_score":0.2432142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01584460990961326,"score_gpt":0.2012533688078092,"score_spread":0.1854087588981959,"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."}}