{"id":"W4235276132","doi":"10.2139/ssrn.3809532","title":"Consistent Local Spectrum (Lcm) Inference for Predictive Return Regressions","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Inference; Econometrics; Spectrum (functional analysis); Predictive inference; Statistics; Computer science; Mathematics; Artificial intelligence; Frequentist inference; Bayesian inference; Bayesian probability; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004523339,0.0001337998,0.0001616599,0.00004402578,0.0004402687,0.0001502002,0.0005570634,0.00006260541,0.00001056279],"category_scores_gemma":[0.00006313652,0.0001106405,0.0001456022,0.0003322689,0.00006217236,0.0002391744,0.0001451879,0.00109592,0.000009319016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003525471,"about_ca_system_score_gemma":0.002497113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000532393,"about_ca_topic_score_gemma":0.0002491165,"domain_scores_codex":[0.9976817,0.0000681775,0.0002576694,0.0003312912,0.0002151916,0.001445973],"domain_scores_gemma":[0.9989845,0.0001883105,0.0001454299,0.0003651638,0.0001798504,0.0001367341],"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":[0.00001360678,0.00007581877,0.0001257173,0.000002942604,0.0000678565,0.00001037138,0.00005001009,0.0007492077,0.0003361412,0.9663408,0.0007902973,0.03143718],"study_design_scores_gemma":[0.0005957675,0.0003530341,0.00024219,0.00005718442,0.00003035047,0.001081358,0.0003014576,0.08280123,0.001640105,0.899593,0.01308022,0.0002241045],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003267308,0.001766689,0.9847386,0.009207428,0.0002642618,0.0001535565,0.00000465657,0.00005914698,0.0005383761],"genre_scores_gemma":[0.9925235,0.001752032,0.003253455,0.000352513,0.0003118864,0.00003444952,0.000005122837,0.000011524,0.001755503],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9892562,"threshold_uncertainty_score":0.4761288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01322821196664172,"score_gpt":0.264581896913095,"score_spread":0.2513536849464533,"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."}}