{"id":"W3122870727","doi":"","title":"Hierarchical Information and the Rate of Information Diffusion","year":2009,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inefficiency; Diffusion; Market microstructure; Momentum (technical analysis); Noise (video); Function (biology); Economics; Econometrics; Microeconomics; Financial economics; Business; Computer science; Finance; Artificial intelligence","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":[0.007293154,0.0006009042,0.001497494,0.003663444,0.001060269,0.006303474,0.001927416,0.003512989,0.02745042],"category_scores_gemma":[0.06895497,0.0008355177,0.0009255493,0.004109984,0.003640453,0.01178391,0.001899517,0.002573919,0.004012257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003869508,"about_ca_system_score_gemma":0.001050533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003964642,"about_ca_topic_score_gemma":0.001669078,"domain_scores_codex":[0.9970707,0.001042475,0.000185622,0.0007514008,0.0005934483,0.0003563251],"domain_scores_gemma":[0.9338225,0.05094884,0.005497449,0.005191703,0.003141551,0.001397871],"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":[0.0001044674,0.00002874576,0.002622781,0.0002114045,0.00007598131,0.0001333548,0.0004706439,0.01910143,0.000563317,0.945676,0.007388133,0.02362371],"study_design_scores_gemma":[0.00002947098,0.00003795768,0.003212121,0.00007830893,0.00004437974,0.000217245,0.0001104019,0.08445198,0.0002329651,0.9069628,0.004573875,0.0000484125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2903889,0.0223325,0.4483507,0.02824184,0.0009379741,0.0003569468,0.00457173,0.001676587,0.2031427],"genre_scores_gemma":[0.936659,0.007832595,0.01738803,0.0005111095,0.0007228284,0.0002414914,0.0009536759,0.0002454497,0.03544586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02745042,"threshold_uncertainty_score":0.09183079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01926199737264202,"score_gpt":0.2463653252860287,"score_spread":0.2271033279133867,"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."}}