{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006832402,0.000163512,0.000302538,0.0000821681,0.0002605512,0.0002521838,0.0006586974,0.00004336011,0.0008256244],"category_scores_gemma":[0.00106263,0.0001400634,0.0001484397,0.0003388184,0.0002763143,0.0007206463,0.0001620859,0.0002079378,0.001958508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005064323,"about_ca_system_score_gemma":0.00004222149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002019876,"about_ca_topic_score_gemma":0.00006084591,"domain_scores_codex":[0.9983964,0.000162208,0.0006286167,0.0004965413,0.0001106826,0.0002055825],"domain_scores_gemma":[0.9971129,0.001828862,0.0003841684,0.0003558459,0.0001266308,0.0001915685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007751481,0.00009139819,0.01458958,0.000008395648,0.0001070115,0.000003562693,0.01443046,0.1422505,0.0001611627,0.792919,0.008191892,0.02716948],"study_design_scores_gemma":[0.0001705741,0.00006686406,0.01810517,0.00001193216,0.000009605865,0.00000139177,0.01018791,0.8709158,0.0004040673,0.09021666,0.009727279,0.0001827118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7262018,0.0000118198,0.2653014,0.002067271,0.0002247348,0.0001508131,0.0000737498,0.00004188488,0.005926429],"genre_scores_gemma":[0.9885312,0.000004248448,0.009937726,0.0009467902,0.00009487259,0.00002788215,0.00001169978,0.0000177579,0.0004277689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7286653,"threshold_uncertainty_score":0.9988186,"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."}}