{"id":"W4381741017","doi":"10.1007/s13235-023-00504-z","title":"Mixed Market Structure and R &D: A Differential Game Approach","year":2023,"lang":"en","type":"article","venue":"Dynamic Games and Applications","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Japan Society for the Promotion of Science; McGill University","keywords":"Nash equilibrium; Markov perfect equilibrium; Differential game; Economics; Microeconomics; Stock (firearms); Sequential game; Outcome (game theory); Markov chain; Mathematical economics; Game theory; Computer science; Mathematics; Mathematical optimization","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":[0.001254545,0.001199556,0.00174498,0.0010155,0.000898256,0.002926385,0.00244868,0.00318033,0.009490077],"category_scores_gemma":[0.003443199,0.0008765102,0.001361088,0.0008907222,0.002515632,0.002713091,0.001964318,0.001595547,0.0006874236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004017482,"about_ca_system_score_gemma":0.00190973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.012756,"about_ca_topic_score_gemma":0.007889263,"domain_scores_codex":[0.9989078,0.000518501,0.00002751713,0.0001836691,0.0001553638,0.0002071102],"domain_scores_gemma":[0.9980707,0.001208758,0.0002827981,0.0000669224,0.0001523322,0.0002185799],"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":[0.00007431334,0.00008740516,0.0005372332,0.00007064177,0.00006184645,0.0002738546,0.00007524656,0.6003003,0.0008728179,0.3941589,0.0009666698,0.002520743],"study_design_scores_gemma":[0.00007065023,0.00004474543,0.0001560045,0.0000120852,0.00001911636,0.00003652246,0.00003587793,0.9134323,0.000104752,0.08476686,0.001302615,0.00001853574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1522159,0.001146976,0.76719,0.004648179,0.0002076141,0.0002820029,0.0009717894,0.0001618801,0.07317565],"genre_scores_gemma":[0.9415876,0.0006694884,0.02995914,0.0003435954,0.0001111992,0.0003759711,0.0001666998,0.00003141615,0.02675488],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.012756,"threshold_uncertainty_score":0.03174746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05055423475242546,"score_gpt":0.2433475247154178,"score_spread":0.1927932899629924,"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."}}