{"id":"W3028421309","doi":"10.2139/ssrn.3041709","title":"Sentiment, Loss Firms, and Investor Expectations of Future Earnings","year":2017,"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":"Quest University Canada","funders":"","keywords":"Earnings; Business; Sentiment analysis; Monetary economics; Financial economics; Accounting; Economics; Computer science; Artificial intelligence","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":[0.001419334,0.0001621306,0.0001876852,0.0003435172,0.0002192471,0.002037321,0.0002229693,0.0009572615,0.003812796],"category_scores_gemma":[0.01127819,0.0001359002,0.0002042121,0.0002505238,0.0003363108,0.0009880513,0.0005353464,0.001008659,0.0004243675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005105323,"about_ca_system_score_gemma":0.0001997642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001982589,"about_ca_topic_score_gemma":0.003091627,"domain_scores_codex":[0.9998325,0.00003931695,0.00001809767,0.00002582625,0.00003762406,0.00004649789],"domain_scores_gemma":[0.9902958,0.003881013,0.004065073,0.0002155342,0.0004167402,0.0011259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009401458,0.0002858869,0.9810434,0.00002328933,0.0000850596,0.0002509321,0.0003827341,0.00235178,0.00102952,0.003364481,0.001069992,0.009172738],"study_design_scores_gemma":[0.00002558088,0.0001634295,0.9870531,0.0000156966,0.00004621875,0.0001071753,0.0005421822,0.007143689,0.0002168256,0.004267692,0.0004005055,0.00001778227],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960991,0.0001141268,0.0002203147,0.000356795,0.000008908572,0.00000359415,0.00008385738,0.000004160474,0.003109107],"genre_scores_gemma":[0.9993854,0.00004591447,0.00002561914,0.00002812368,0.0000149465,0.000001127122,0.00006860864,0.000001654139,0.0004286288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003812796,"threshold_uncertainty_score":0.01275504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01390906874980332,"score_gpt":0.2218539023588951,"score_spread":0.2079448336090917,"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."}}