{"id":"W4391608123","doi":"10.2139/ssrn.4719093","title":"Tail Similarity","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Similarity (geometry); 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":[0.0005283484,0.0004565313,0.0007373632,0.001734758,0.001062304,0.002395996,0.0007978244,0.00168384,0.04086627],"category_scores_gemma":[0.004218399,0.0002424413,0.0006431138,0.00111462,0.0005938485,0.002577305,0.001850087,0.001395805,0.01189773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005338959,"about_ca_system_score_gemma":0.0004860763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005374098,"about_ca_topic_score_gemma":0.000525409,"domain_scores_codex":[0.9994261,0.00005581028,0.00002743454,0.0002237209,0.0001564098,0.0001105577],"domain_scores_gemma":[0.9982326,0.0002488915,0.0001771576,0.000606889,0.000451385,0.0002830552],"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":[0.0009105545,0.0004021177,0.01085626,0.0003274271,0.0001528722,0.000763573,0.0003974865,0.02162952,0.08237702,0.5358486,0.04557093,0.3007638],"study_design_scores_gemma":[0.00007538574,0.0003295041,0.01815988,0.00008490846,0.0001115353,0.002646776,0.0003791018,0.2427658,0.03708404,0.6445491,0.05368249,0.0001315719],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2920637,0.001548134,0.3565209,0.001396434,0.001270802,0.0003216328,0.003226734,0.00441296,0.3392387],"genre_scores_gemma":[0.8868961,0.0004969864,0.01784806,0.0009539486,0.000447971,0.0001147753,0.003088416,0.0007840893,0.08936981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04086627,"threshold_uncertainty_score":0.1367114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02980796557307502,"score_gpt":0.2426540712216298,"score_spread":0.2128461056485547,"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."}}