{"id":"W1899286130","doi":"10.3968/j.sms.1923845220110301.4z483","title":"Study on Linear Correlation Coefficient and Nonlinear Correlation Coefficient in Mathematical Statistics","year":2011,"lang":"en","type":"article","venue":"Studies in mathematical sciences","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Correlation coefficient; Mathematics; Linear predictor function; Fisher transformation; Statistics; Simple linear regression; Nonlinear system; Correlation; Distance correlation; Linear regression; Simple (philosophy); Linear correlation; Pearson product-moment correlation coefficient; Correlation ratio; Linear model; Simple correlation; Linear relationship; Proper linear model; Regression analysis; Polynomial regression; Random variable; Physics; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0150183,0.001596334,0.001520272,0.004828026,0.001248164,0.003819848,0.001966877,0.002384379,0.003909091],"category_scores_gemma":[0.07875896,0.0005760163,0.001375054,0.009373164,0.004073265,0.009672222,0.002536808,0.004743806,0.002036586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002523245,"about_ca_system_score_gemma":0.003113267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002531523,"about_ca_topic_score_gemma":0.001191661,"domain_scores_codex":[0.9802408,0.007771092,0.001087357,0.003684906,0.006361614,0.0008541959],"domain_scores_gemma":[0.9327648,0.05092399,0.003372116,0.003809005,0.008645869,0.0004842473],"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":[0.0001517132,0.00009596124,0.01664721,0.001061571,0.0003511207,0.0007929304,0.001127132,0.05010875,0.002302093,0.7049337,0.02025107,0.2021768],"study_design_scores_gemma":[0.00004163655,0.0002390048,0.008232147,0.0006398144,0.0003105427,0.002401551,0.0006547809,0.3389665,0.003795342,0.5584897,0.08592292,0.0003060555],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01526427,0.02245886,0.9359733,0.003132224,0.001126587,0.0001231786,0.0003263809,0.0004728821,0.02112238],"genre_scores_gemma":[0.5955457,0.05127441,0.3286135,0.003039154,0.005836999,0.0009777548,0.001477503,0.0009467059,0.01228821],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0150183,"threshold_uncertainty_score":0.07942533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08093275213433856,"score_gpt":0.3490408168423891,"score_spread":0.2681080647080505,"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."}}