{"id":"W4200414590","doi":"10.3390/jrfm14120582","title":"Analysis of the Financial Information Contained in the Texts of Current Reports: A Deep Learning Approach","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ambiguity; Meaning (existential); Class (philosophy); Sentiment analysis; Context (archaeology); Computer science; Financial market; Investment decisions; Investment (military); Artificial intelligence; Event (particle physics); Finance; Data science; Economics; Psychology; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008016297,0.0005955314,0.0004163508,0.002711695,0.0002778137,0.001001291,0.0004987058,0.0007473429,0.001162009],"category_scores_gemma":[0.002050323,0.0002284945,0.000525778,0.001499915,0.0003318672,0.001063869,0.0006066374,0.001008174,0.0004521438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005532525,"about_ca_system_score_gemma":0.000666072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003094398,"about_ca_topic_score_gemma":0.003572284,"domain_scores_codex":[0.9996799,0.00007255706,0.00004087891,0.00006461863,0.00009055399,0.00005144973],"domain_scores_gemma":[0.9990563,0.0004874342,0.0001526015,0.00004467377,0.0002168387,0.00004213938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003010337,0.0004837477,0.01050075,0.0002796899,0.0001315019,0.0004300576,0.0004799057,0.09369058,0.0259838,0.006509862,0.004465015,0.8567441],"study_design_scores_gemma":[0.000007655774,0.00005302501,0.003202155,0.00003762171,0.00003236063,0.00005493752,0.0001078668,0.9857627,0.003630624,0.005668629,0.001429572,0.00001287697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2277572,0.00182503,0.7612127,0.002038977,0.0001626389,0.0001498211,0.001040857,0.001108427,0.00470438],"genre_scores_gemma":[0.8104848,0.001447947,0.1808443,0.0002244976,0.0002163614,0.0001157226,0.00189286,0.00005166007,0.004721836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003094398,"threshold_uncertainty_score":0.006152809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03465133891225478,"score_gpt":0.3288584954365784,"score_spread":0.2942071565243236,"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."}}