{"id":"W2945166501","doi":"","title":"Time Series Analysis of National League Slugging Percentage (Major League Baseball)","year":2017,"lang":"en","type":"article","venue":"Student Research Proceedings","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Autocorrelation; Partial autocorrelation function; Series (stratigraphy); Statistics; Autoregressive model; Time series; Slugging; Econometrics; Mathematics; Autoregressive integrated moving average; Plot (graphics); Moving average","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":[0.0008843818,0.000322383,0.0002734308,0.002218276,0.0001627184,0.0005313017,0.0002640792,0.0002090257,0.002350322],"category_scores_gemma":[0.003225941,0.00006810603,0.0004112739,0.003301459,0.0001127934,0.0003495942,0.000242996,0.0004340153,0.0006615635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005939473,"about_ca_system_score_gemma":0.0004027232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01469328,"about_ca_topic_score_gemma":0.01266478,"domain_scores_codex":[0.9995342,0.00007826855,0.00004533855,0.00009915834,0.0001965151,0.00004649063],"domain_scores_gemma":[0.9984628,0.0005036773,0.0003376177,0.0001094925,0.0005130357,0.0000733459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000514889,0.0003803418,0.7229567,0.0003705155,0.0003202393,0.000518525,0.001252925,0.04625264,0.009757112,0.003648034,0.006361293,0.2076668],"study_design_scores_gemma":[0.000006154584,0.0002998104,0.9440227,0.00004125734,0.00005404732,0.0001454735,0.0007337481,0.04249574,0.004453286,0.0004223434,0.007294499,0.00003100715],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9723006,0.0002500724,0.009888677,0.0001236973,0.00005529143,0.0001003101,0.01017978,0.0002929051,0.006808698],"genre_scores_gemma":[0.9799059,0.0002044341,0.006537553,0.00001164419,0.0000188868,0.00009348079,0.01068166,0.00002368194,0.00252276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01469328,"threshold_uncertainty_score":0.02921551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1140900197023311,"score_gpt":0.3765296638247516,"score_spread":0.2624396441224205,"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."}}