{"id":"W4387118843","doi":"10.1007/s00780-023-00519-9","title":"Present-biased lobbyists in linear–quadratic stochastic differential games","year":2023,"lang":"en","type":"article","venue":"Finance and Stochastics","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; Social Sciences and Humanities Research Council of Canada; National Natural Science Foundation of China; National Science Foundation","keywords":"Mathematical economics; Commit; Constant (computer programming); Quadratic equation; Economics; Stochastic differential equation; Differential game; Strategy; Mathematics; Applied mathematics; Game theory; Mathematical optimization; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005248522,0.001009842,0.003711438,0.001074229,0.001272472,0.004272245,0.00250025,0.00515586,0.01307883],"category_scores_gemma":[0.02076893,0.001285967,0.0009925035,0.0008832003,0.004027827,0.003327734,0.002902664,0.003231515,0.0007704389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003071583,"about_ca_system_score_gemma":0.001818462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009554841,"about_ca_topic_score_gemma":0.009723621,"domain_scores_codex":[0.99788,0.001093485,0.00006959603,0.0002599591,0.0001841241,0.0005128855],"domain_scores_gemma":[0.9805177,0.01509838,0.001750136,0.0004605489,0.0006571208,0.001515993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000444444,0.0001612937,0.003702439,0.0002013956,0.000169651,0.0004320406,0.0004680431,0.1974088,0.001128908,0.7791389,0.008439843,0.008304124],"study_design_scores_gemma":[0.0002023581,0.00008800995,0.001290231,0.00004925394,0.00006651239,0.0001048148,0.0003535448,0.4884416,0.000214318,0.50769,0.001438779,0.00006053499],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.640259,0.001787879,0.2658945,0.01899208,0.0003503613,0.0002178373,0.0007438518,0.0002985272,0.07145587],"genre_scores_gemma":[0.9742569,0.0004051818,0.002704893,0.0004601275,0.0001102592,0.00007074828,0.00007200852,0.00003536808,0.02188461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01307883,"threshold_uncertainty_score":0.04375309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07759853147720953,"score_gpt":0.2685522406065499,"score_spread":0.1909537091293404,"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."}}