{"id":"W1942596096","doi":"10.2139/ssrn.2009192","title":"Formal Identification of Sentiment Effects in Asset Markets","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Identification (biology); Business; Asset (computer security); Financial economics; Economics; Financial system; Monetary economics; Computer science; Computer security","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":[0.003265071,0.0005483232,0.001102457,0.001081889,0.0005219887,0.002273558,0.0007719411,0.001282936,0.01032158],"category_scores_gemma":[0.01779059,0.000513028,0.0007972266,0.0006517765,0.001445105,0.004593977,0.00152818,0.001318583,0.0005629634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004871548,"about_ca_system_score_gemma":0.0007983715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008236718,"about_ca_topic_score_gemma":0.0009295377,"domain_scores_codex":[0.9992892,0.0003145678,0.00005181416,0.00009928996,0.0001176468,0.0001274389],"domain_scores_gemma":[0.9910979,0.006455623,0.0009790099,0.0006261236,0.0005396777,0.0003016395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008352294,0.0001530553,0.004120609,0.0001403966,0.00004296978,0.000248034,0.0002431951,0.01131318,0.002670209,0.9631613,0.001458906,0.01636476],"study_design_scores_gemma":[0.00007119845,0.00005757117,0.003578957,0.00004447843,0.00003310934,0.00008052529,0.0001003198,0.1904582,0.0008461511,0.8035071,0.001204967,0.00001735897],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4902399,0.0006298499,0.4633119,0.00140888,0.000143816,0.0001786601,0.000425433,0.000474912,0.04318667],"genre_scores_gemma":[0.9819837,0.0002865202,0.01400903,0.00008546041,0.0001569011,0.00005482742,0.0001927242,0.00003719061,0.0031937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01032158,"threshold_uncertainty_score":0.03452915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009885676833657535,"score_gpt":0.2129163989081599,"score_spread":0.2030307220745023,"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."}}