{"id":"W6939120909","doi":"10.6068/dp157763474df64","title":"TREND: Federal Housing Finance Agency. House Price Index: House Price Index - Purchase Only | State: South Carolina | Metropolitan Statistical Area: 1790 | Metropolitan Statistical Area: Columbia, SC | Seasonally Adjusted: Seasonally Adj, 1991/1 - 2016/1. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 057-001-002","year":2016,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Underwriting; Metropolitan area; Index (typography); Quarter (Canadian coin); House price; Mortgage insurance; Loan; Securitization","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":[0.0008084202,0.001605118,0.001214523,0.003477563,0.0009658598,0.002091935,0.002370752,0.001096949,0.09627641],"category_scores_gemma":[0.007097766,0.0007041439,0.0008404272,0.009336773,0.0002981042,0.001995552,0.001519022,0.002158691,0.1489379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002277997,"about_ca_system_score_gemma":0.003491445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1278704,"about_ca_topic_score_gemma":0.1552817,"domain_scores_codex":[0.9987552,0.0001270671,0.0001540119,0.0003587737,0.0004461951,0.0001586907],"domain_scores_gemma":[0.9945464,0.0004783438,0.0005879118,0.0006849707,0.003366631,0.0003357077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001347199,0.000008809056,0.001039674,0.00008721522,0.000007681248,0.000004311975,0.000007177348,0.0000607414,0.00001447536,0.0001744272,0.9971508,0.001431201],"study_design_scores_gemma":[0.0001047139,0.00001548363,0.01505487,0.0002192935,0.00001767353,0.00002127381,0.0001374774,0.0004186355,0.0001582274,0.0006048967,0.9832214,0.00002599707],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009830105,0.00001571247,0.00003280746,0.00004114475,0.00001759732,0.00001021626,0.9989833,0.00007199414,0.0007289025],"genre_scores_gemma":[0.0003307293,0.00002560412,0.00009968942,0.00002961517,0.0000114987,0.00007824981,0.9981958,0.00003169911,0.001197095],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1278704,"threshold_uncertainty_score":0.3220767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02475125763903434,"score_gpt":0.2749989844266463,"score_spread":0.2502477267876119,"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."}}