{"id":"W4389288586","doi":"10.22214/ijraset.2023.57267","title":"Autonomous Parking Surveillance","year":2023,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"License; Identification (biology); Computer science; Parking lot; Parking guidance and information; Simple (philosophy); Computer security; Transport engineering; Engineering; Operating system","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":[0.0001928986,0.0003476643,0.000357198,0.0006313331,0.000241184,0.0004623435,0.0005990958,0.0003869123,0.003952641],"category_scores_gemma":[0.0003344332,0.0001590797,0.000183569,0.0002752295,0.0001260437,0.0004249835,0.0006435537,0.0002168707,0.002055287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001698152,"about_ca_system_score_gemma":0.0004421852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001350496,"about_ca_topic_score_gemma":0.001677122,"domain_scores_codex":[0.9998357,0.00002222932,0.000006271815,0.00004910006,0.00005588696,0.00003063895],"domain_scores_gemma":[0.9998061,0.00002060094,0.00001771727,0.00003441044,0.00008952105,0.00003166678],"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":[0.001326403,0.0003171299,0.02265212,0.0003345496,0.00008702797,0.0007309219,0.0003598406,0.02468769,0.1773392,0.003082226,0.04260086,0.726482],"study_design_scores_gemma":[0.0001457982,0.0005217754,0.03290095,0.00006404731,0.0001011237,0.001570867,0.0002530177,0.785969,0.1329178,0.003286034,0.04217288,0.00009683443],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.457581,0.0007336116,0.4783759,0.0003450315,0.0003515864,0.0002994323,0.002779418,0.02748617,0.032048],"genre_scores_gemma":[0.9512789,0.00008503559,0.04058083,0.00009804782,0.00003873843,0.00006671109,0.001327521,0.00009173064,0.006432498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003952641,"threshold_uncertainty_score":0.01322293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.063761209262836,"score_gpt":0.3839912224599538,"score_spread":0.3202300131971177,"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."}}