{"id":"W4285086941","doi":"10.26509/frbc-wp-202128r","title":"Communicating Data Uncertainty: Multi-Wave Experimental Evidence for UK GDP","year":2022,"lang":"en","type":"report","venue":"Working paper","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"Warwick Business School, University of Warwick; University of Warwick","keywords":"Probabilistic logic; Point estimation; Measurement uncertainty; Econometrics; Qualitative property; Control (management); Point (geometry); Statistics; Computer science; Economics; Mathematics; Artificial intelligence","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":["metaresearch","metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01441891,0.0005673374,0.001172637,0.0003718092,0.001196966,0.001163276,0.007363723,0.0003909879,0.004897683],"category_scores_gemma":[0.01436456,0.0004848271,0.0004967336,0.0005659671,0.0002201376,0.0004447676,0.007488642,0.001104865,0.0001592923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007995189,"about_ca_system_score_gemma":0.001308759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008568076,"about_ca_topic_score_gemma":0.0009800863,"domain_scores_codex":[0.9917309,0.00041013,0.002159494,0.002166229,0.002864524,0.0006687134],"domain_scores_gemma":[0.9789291,0.01088312,0.001827621,0.007734987,0.0004356929,0.0001894927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001015941,0.0002035527,0.001386979,0.00001460906,0.00005424714,0.00004510022,0.0007956459,0.0004635868,0.0002839764,0.00002838333,0.1508095,0.8458128],"study_design_scores_gemma":[0.0003679008,0.00008317563,0.0001505074,0.000724863,0.00009056679,0.00007536254,0.001989367,0.003175715,0.00002119689,0.0007245201,0.991931,0.0006658621],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2781446,0.2486337,0.01086363,0.007508575,0.1310007,0.01797128,0.01206963,0.002212887,0.291595],"genre_scores_gemma":[0.9138802,0.001403558,0.04833871,0.001130773,0.001423923,0.0005149735,0.001223573,0.0002468999,0.03183741],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.845147,"threshold_uncertainty_score":0.9998736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8489929296110112,"score_gpt":0.5691288876152597,"score_spread":0.2798640419957515,"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."}}