{"id":"W4412877150","doi":"10.1145/3711896.3737268","title":"Timing is Important: Risk-aware Fund Allocation based on Time-Series Forecasting","year":2025,"lang":"en","type":"article","venue":"","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"Shenzhen Technology University; Tencent","keywords":"Computer science; Series (stratigraphy); Time series; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001973856,0.001041996,0.001117426,0.0006741227,0.0003147415,0.001178009,0.001305516,0.0008736352,0.001459869],"category_scores_gemma":[0.007157317,0.0003067267,0.0004801093,0.0008452458,0.0003313554,0.001877852,0.0008603205,0.00162526,0.0004666792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005901898,"about_ca_system_score_gemma":0.001254653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005293035,"about_ca_topic_score_gemma":0.004822514,"domain_scores_codex":[0.9993569,0.0001774149,0.00003954762,0.0001970766,0.0001489322,0.00008011904],"domain_scores_gemma":[0.9980756,0.0009975354,0.0002772199,0.0002706254,0.0002286191,0.0001504755],"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":[0.00075719,0.0003012396,0.009988505,0.0001507067,0.0001412799,0.0001890092,0.00009867122,0.7338144,0.003935776,0.006924833,0.01222603,0.2314723],"study_design_scores_gemma":[0.00002362975,0.00003107094,0.0008144551,0.000009752041,0.00001583764,0.00003341312,0.00001232153,0.993493,0.0009431446,0.003814847,0.0007999526,0.00000864668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2264276,0.004097081,0.7463941,0.002872976,0.0006375737,0.0001739637,0.001617902,0.007481827,0.01029704],"genre_scores_gemma":[0.8736069,0.0007770504,0.1205871,0.0003963291,0.000281172,0.00007981269,0.001609338,0.000217869,0.002444455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005293035,"threshold_uncertainty_score":0.01052445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1014861500166915,"score_gpt":0.2440826699075851,"score_spread":0.1425965198908936,"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."}}