{"id":"W4230281295","doi":"10.22237/jmasm/1493599440","title":"Front Matter","year":2017,"lang":"en","type":"paratext","venue":"Journal of Modern Applied Statistical Methods","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003156169,0.0005211384,0.001785554,0.0004074238,0.0001969004,0.0009180303,0.004787795,0.0004111205,0.006835548],"category_scores_gemma":[0.0003809097,0.0004054766,0.0003138536,0.00009135105,0.0001981934,0.0003793643,0.0008470768,0.001579465,0.01335207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001731214,"about_ca_system_score_gemma":0.0004783276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009121937,"about_ca_topic_score_gemma":0.000001160517,"domain_scores_codex":[0.9954884,0.0007070534,0.001451933,0.0006837581,0.001100559,0.0005682857],"domain_scores_gemma":[0.9933869,0.001427741,0.002412363,0.001967815,0.0003268419,0.000478382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000343097,0.00006702441,0.000001265251,0.00006657269,0.0003056987,0.00007481261,0.00008006419,0.00009642611,0.0003202238,0.007172475,0.6404458,0.3513353],"study_design_scores_gemma":[0.0009319796,0.0001735891,0.000287518,0.0001994432,0.0005858907,0.0002578764,0.000006837703,0.04622975,0.0005232316,0.2096158,0.7401546,0.001033467],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[3.708457e-7,0.0007897037,0.8218647,0.0003305234,0.002065546,0.0001207006,0.0001919743,0.000009857744,0.1746267],"genre_scores_gemma":[0.0002084257,0.0001281313,0.9653017,0.0006264281,0.0007361738,0.00001108192,0.0000401666,0.00005316965,0.03289476],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3503019,"threshold_uncertainty_score":0.9998397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04515406346335576,"score_gpt":0.4003509801400259,"score_spread":0.3551969166766701,"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."}}