{"id":"W2791604340","doi":"10.4236/ojs.2018.81010","title":"A Chi-Square Approximation for the <i>F</i> Distribution","year":2018,"lang":"en","type":"article","venue":"Open Journal of Statistics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Mathematics; Statistics; Distribution (mathematics); F-distribution; Square (algebra); Chi-square test; Statistic; Normal distribution; Cumulative distribution function; Combinatorics; Mathematical analysis; Probability distribution; Probability density function","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":[0.01311178,0.001696234,0.001589764,0.003256741,0.001138376,0.002085377,0.003774278,0.002845198,0.0175297],"category_scores_gemma":[0.08366045,0.0006412776,0.001504152,0.003871022,0.003523917,0.004112252,0.00190841,0.005613671,0.01104531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001309919,"about_ca_system_score_gemma":0.002175839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004180878,"about_ca_topic_score_gemma":0.003007866,"domain_scores_codex":[0.9909269,0.003713015,0.0003839881,0.001602805,0.002899249,0.0004741308],"domain_scores_gemma":[0.9547998,0.03287425,0.001725298,0.004828106,0.005308405,0.0004641371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004185395,0.0002548111,0.01004679,0.0009881611,0.0002672042,0.001575893,0.001467544,0.07476992,0.01293834,0.4072825,0.03599971,0.4539905],"study_design_scores_gemma":[0.00009155482,0.0003517999,0.006505436,0.0003158074,0.0001063921,0.002774366,0.0004387115,0.6778409,0.00949968,0.2550317,0.04683367,0.000209947],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002051298,0.0002647609,0.9953288,0.0001807288,0.0001246346,0.00006503626,0.0001365337,0.0005641373,0.001284039],"genre_scores_gemma":[0.1584664,0.00126335,0.8237025,0.0006790165,0.0006324411,0.001347569,0.00139263,0.001090024,0.01142597],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0175297,"threshold_uncertainty_score":0.06934255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1501519387144394,"score_gpt":0.4154162127582547,"score_spread":0.2652642740438153,"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."}}