{"id":"W4375953126","doi":"10.22214/ijraset.2023.51487","title":"Used Car Price Prediction Using Machine Learning","year":2023,"lang":"en","type":"article","venue":"International Journal for Research in Applied Science and Engineering Technology","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006469582,0.001336262,0.001203374,0.002981019,0.0004135774,0.001340176,0.001582061,0.001248182,0.0118151],"category_scores_gemma":[0.002562691,0.0004138476,0.001371444,0.001896908,0.0002349704,0.001325905,0.000553744,0.001665665,0.004906591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001123147,"about_ca_system_score_gemma":0.0006773746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02430354,"about_ca_topic_score_gemma":0.01764078,"domain_scores_codex":[0.9996135,0.00005847064,0.00003164474,0.0001434915,0.00007016797,0.0000827],"domain_scores_gemma":[0.9989667,0.0004832785,0.00009316614,0.00008868062,0.0003019608,0.0000662335],"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":[0.0005614,0.001058156,0.03884131,0.0002079965,0.0002881826,0.0003629834,0.00002904357,0.5765054,0.0005419629,0.002380826,0.02647485,0.3527479],"study_design_scores_gemma":[0.000007366437,0.00001665895,0.001104947,0.000007582832,0.000008548396,0.00001332816,0.000007029131,0.9972482,0.0001124155,0.0007773574,0.0006917501,0.000004736092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5676557,0.007070719,0.3439169,0.00466392,0.002806511,0.0005969778,0.02105124,0.01091134,0.04132659],"genre_scores_gemma":[0.9414414,0.0007981774,0.03154778,0.0002985068,0.0004030228,0.0001302876,0.01240256,0.00009751507,0.01288064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02430354,"threshold_uncertainty_score":0.04832417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05693453243042489,"score_gpt":0.3558094187355608,"score_spread":0.2988748863051359,"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."}}