{"id":"W4250867380","doi":"10.2139/ssrn.2200485","title":"A Markov Switching Approach to Herding","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University; Balsillie School of International Affairs","funders":"","keywords":"Herding; Markov chain; Computer science; Business; Economics; Econometrics; Geography; 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":[0.002684697,0.0007689561,0.002570439,0.002164847,0.001300562,0.002485735,0.004219871,0.003711333,0.01251725],"category_scores_gemma":[0.01166293,0.001259032,0.002188999,0.002054358,0.002600461,0.004434881,0.00206857,0.003169481,0.000838346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00246824,"about_ca_system_score_gemma":0.001562727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01471196,"about_ca_topic_score_gemma":0.01186322,"domain_scores_codex":[0.9987482,0.0006306331,0.00005698553,0.000214343,0.0001749412,0.0001748758],"domain_scores_gemma":[0.9917459,0.006608417,0.0005094346,0.0003841677,0.0004225172,0.0003295479],"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":[0.00005156746,0.0000747213,0.001052288,0.00009074881,0.0001124716,0.0001562029,0.0001527679,0.3084938,0.0003370686,0.67615,0.003180282,0.01014809],"study_design_scores_gemma":[0.00002036952,0.0000174596,0.00020573,0.00001199385,0.00002427646,0.00002976261,0.00002550881,0.7880389,0.00003141721,0.210889,0.0006878954,0.00001769414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04302531,0.001374199,0.9366205,0.002564104,0.0003215458,0.00007566515,0.0004305636,0.0002802642,0.01530791],"genre_scores_gemma":[0.8445491,0.0031459,0.1031426,0.0007032232,0.0009195596,0.0003596961,0.000595886,0.000234937,0.04634911],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01471196,"threshold_uncertainty_score":0.04187435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01475044926229072,"score_gpt":0.25488388603817,"score_spread":0.2401334367758793,"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."}}