{"id":"W4240504270","doi":"10.3386/w18724","title":"Measuring Margin","year":2013,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Margin (machine learning); Geology; Geography; Computer science; Machine learning","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006072694,0.0002489391,0.0008445583,0.001804033,0.000196354,0.0001212331,0.000665166,0.0005540227,0.003639893],"category_scores_gemma":[0.002126951,0.0003108004,0.0003367259,0.0003047534,0.0002625494,0.0002773954,0.0002202792,0.0008051126,0.004918772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002650544,"about_ca_system_score_gemma":0.001927809,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006680768,"about_ca_topic_score_gemma":0.0002396232,"domain_scores_codex":[0.9966455,0.000040933,0.001498406,0.0007270426,0.0005498212,0.000538304],"domain_scores_gemma":[0.9967047,0.0004516698,0.0007815124,0.000503229,0.001416144,0.0001427708],"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":[0.000008055985,0.00005659471,0.007558441,0.00009548038,0.0001002925,0.000001017622,0.00003869104,0.0001872468,0.000006016517,0.8062376,0.1843462,0.001364342],"study_design_scores_gemma":[0.0002458929,0.00003841348,0.02416958,0.00006541133,0.000003758347,0.00000631895,0.00001384244,0.0005876856,0.00002556147,0.5993056,0.3752643,0.000273648],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.00504413,0.004042712,0.0000563459,0.0005876544,0.001423434,0.0005998046,0.0006286127,0.00002329471,0.987594],"genre_scores_gemma":[0.9103165,0.004496405,0.0005645878,0.000007795869,0.003408249,0.000313441,0.0007363216,0.0001149458,0.08004176],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9075522,"threshold_uncertainty_score":0.9999344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6096209847576881,"score_gpt":0.4742770133657718,"score_spread":0.1353439713919163,"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."}}