{"id":"W2989622118","doi":"10.2139/ssrn.3470974","title":"Discovering Fundamental Value","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal; Queen's University","funders":"","keywords":"Value (mathematics); Mathematics; Statistics","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":[0.0005946916,0.0005460258,0.0006733544,0.002882799,0.0005456382,0.001701365,0.0008989387,0.00110217,0.0063748],"category_scores_gemma":[0.007542068,0.0003186806,0.000651302,0.001109798,0.0006680185,0.003681535,0.001209685,0.00151037,0.001467029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005052183,"about_ca_system_score_gemma":0.0006449933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006801903,"about_ca_topic_score_gemma":0.0005466195,"domain_scores_codex":[0.9995571,0.00006528763,0.0000199895,0.0001502539,0.0001524453,0.00005490424],"domain_scores_gemma":[0.9977564,0.00127442,0.0002107907,0.0003909236,0.0002670643,0.0001004737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004793684,0.0002759186,0.01679705,0.0002451302,0.0001302394,0.0004428138,0.0004484495,0.0314422,0.02464696,0.2898044,0.01775793,0.6175295],"study_design_scores_gemma":[0.00005484473,0.0001387946,0.004346131,0.00005648358,0.00005935493,0.0002937043,0.0001567967,0.502203,0.007730525,0.4733344,0.01158447,0.0000415687],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3815165,0.001863168,0.5795286,0.00220831,0.0005450643,0.0001275713,0.002045702,0.001987399,0.03017768],"genre_scores_gemma":[0.9120981,0.0006735151,0.07949334,0.0001611616,0.0003053323,0.00006437319,0.001651705,0.0001372382,0.005415259],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0063748,"threshold_uncertainty_score":0.02132583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04234556357650118,"score_gpt":0.3720685958038578,"score_spread":0.3297230322273566,"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."}}