{"id":"W7017573234","doi":"","title":"Aspen EPIC discusses income volatility with Fred Wherry","year":2016,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"EPIC; Volatility (finance); Prosperity; Time series; Quarter (Canadian coin)","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":[0.0009682223,0.000499219,0.0002213653,0.0006027194,0.001828091,0.00181698,0.0003387159,0.001113177,0.1149778],"category_scores_gemma":[0.003324646,0.0001610053,0.0001807192,0.0003891718,0.0005031229,0.002383553,0.001372239,0.002014895,0.03524449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000925619,"about_ca_system_score_gemma":0.0008415923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003388131,"about_ca_topic_score_gemma":0.0106467,"domain_scores_codex":[0.9996357,0.00008561245,0.000008044382,0.00005751098,0.0001566615,0.00005638168],"domain_scores_gemma":[0.9989672,0.0003913427,0.00004305963,0.00002627968,0.0001783011,0.0003938422],"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":[0.00000727178,0.000009922875,0.0001229198,0.00001259423,5.458596e-7,0.00004062365,0.000168466,0.00002763498,0.00006111496,0.002018145,0.9863311,0.01119966],"study_design_scores_gemma":[0.000002285697,0.000005356259,0.0002534322,0.00003847491,7.913875e-7,0.00005362083,0.0003556621,0.0001116863,0.0001213134,0.001157723,0.9978951,0.000004531808],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006526406,0.01141846,0.00417227,0.2867747,0.03475668,0.00008357173,0.00182935,0.001596186,0.6528424],"genre_scores_gemma":[0.02971276,0.00732538,0.001660371,0.02896203,0.006357749,0.0000602102,0.0005520319,0.0009828239,0.9243866],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1149778,"threshold_uncertainty_score":0.3846389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00502654660849895,"score_gpt":0.1932390425954366,"score_spread":0.1882124959869376,"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."}}