{"id":"W3042525782","doi":"10.3982/qe923","title":"Estimating local interactions among many agents who observe their neighbors","year":2020,"lang":"en","type":"article","venue":"Quantitative Economics","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Stochastic game; Network formation; Computer science; Best response; Set (abstract data type); Complete information; Inference; Fraction (chemistry); Simple (philosophy); Mathematical economics; Game theory; Process (computing); Artificial intelligence; Mathematics","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":[0.00420561,0.0005923773,0.001177527,0.0009526263,0.0004704901,0.001158965,0.001432633,0.001133126,0.001990906],"category_scores_gemma":[0.01872209,0.0006723365,0.0007171407,0.0009573893,0.001109365,0.002574691,0.001490465,0.001236514,0.000424705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009721415,"about_ca_system_score_gemma":0.0005428448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007408244,"about_ca_topic_score_gemma":0.008815666,"domain_scores_codex":[0.9978745,0.001202655,0.00006334388,0.0005672185,0.0001436999,0.0001486023],"domain_scores_gemma":[0.9876748,0.009640531,0.001425917,0.0006768679,0.0003111392,0.0002706527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004966818,0.000428345,0.1422518,0.00017367,0.0008880706,0.0005119886,0.0009468357,0.7444807,0.002550668,0.0590174,0.0009307112,0.04732313],"study_design_scores_gemma":[0.00003290861,0.0001211475,0.01590971,0.0000255406,0.00009678044,0.00009038702,0.0004762335,0.9440925,0.0008761116,0.03762579,0.00061366,0.00003914985],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6939736,0.000326509,0.3013816,0.0006355121,0.00001619602,0.0001184858,0.0002834382,0.00009150391,0.003173136],"genre_scores_gemma":[0.9810013,0.0001335005,0.01715263,0.00005805215,0.00001307319,0.00006552937,0.0001727589,0.000008855285,0.001394235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007408244,"threshold_uncertainty_score":0.02224165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2662997436238492,"score_gpt":0.4047538449016114,"score_spread":0.1384541012777622,"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."}}