{"id":"W4221120354","doi":"10.1111/rmir.12201","title":"Residential property insurance and markets: Florida's QUASR data","year":2022,"lang":"en","type":"article","venue":"Risk Management and Insurance Review","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Property insurance; Business; Actuarial science; Property market; Quarter (Canadian coin); Imputation (statistics); Residential property; Finance; Insurance policy; Economics; General insurance; Missing data; Real estate","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":[0.001138531,0.0004031557,0.0002777777,0.005398885,0.0005123072,0.0009862798,0.0009061512,0.0006441063,0.01312687],"category_scores_gemma":[0.005396934,0.000229879,0.0003880006,0.006530659,0.0001580787,0.0007009135,0.0008319257,0.0007221196,0.004424432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001301485,"about_ca_system_score_gemma":0.002093848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2350752,"about_ca_topic_score_gemma":0.2193346,"domain_scores_codex":[0.9989941,0.0001102328,0.00008342656,0.0001277308,0.0005294271,0.0001550504],"domain_scores_gemma":[0.9943219,0.0007995145,0.00204133,0.0003541082,0.002093175,0.0003899539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002385456,0.000376592,0.1345573,0.0004014453,0.0001681044,0.0002836917,0.0006004162,0.002297948,0.0007253877,0.004120389,0.803929,0.05230115],"study_design_scores_gemma":[0.0001177734,0.0001317651,0.6203404,0.0001871949,0.00008410173,0.0001811689,0.0008289283,0.002543764,0.000811838,0.0009638924,0.3737284,0.0000807744],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.09824645,0.0007266747,0.0009861047,0.001377141,0.0000487793,0.0002969244,0.8806441,0.0003045493,0.01736929],"genre_scores_gemma":[0.1411887,0.0007968083,0.002491258,0.0004435486,0.0001090727,0.0007765002,0.8441742,0.00007265939,0.009947138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2350752,"threshold_uncertainty_score":0.4674138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03557366662729081,"score_gpt":0.2299062745504813,"score_spread":0.1943326079231905,"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."}}