{"id":"W4306648514","doi":"10.3386/w30561","title":"Segmented Arbitrage","year":2022,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Arbitrage; Business; Computer science; Finance","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":[0.001654591,0.0005745071,0.0008723369,0.002526014,0.0006526539,0.00222753,0.001045498,0.0007443268,0.007603908],"category_scores_gemma":[0.01494304,0.0002994333,0.001134764,0.002509886,0.0009600373,0.003759062,0.001934031,0.0008825883,0.0004730627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008824554,"about_ca_system_score_gemma":0.0007399592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003195501,"about_ca_topic_score_gemma":0.002460747,"domain_scores_codex":[0.9987437,0.000259022,0.00009085671,0.0003202514,0.0003796133,0.000206675],"domain_scores_gemma":[0.9913251,0.00333721,0.003022395,0.001120209,0.0006394249,0.0005556236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003784634,0.0002188997,0.1374795,0.0002723266,0.0005861462,0.001621471,0.001424953,0.1771493,0.00534272,0.5917735,0.007416023,0.07633677],"study_design_scores_gemma":[0.00005164802,0.0001597739,0.04733796,0.00007693016,0.0001154771,0.001030121,0.0003099975,0.5359294,0.002578321,0.4042791,0.008058529,0.00007272419],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7912798,0.001688321,0.1757729,0.0005475368,0.00007142523,0.0002006842,0.002127594,0.0003622017,0.02794955],"genre_scores_gemma":[0.9885501,0.0002325925,0.00824275,0.00002960696,0.00003061091,0.00004999003,0.0006978922,0.00002343439,0.002142956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007603908,"threshold_uncertainty_score":0.02543765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4753044686134188,"score_gpt":0.4961991547885758,"score_spread":0.02089468617515705,"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."}}