{"id":"W1527406032","doi":"10.5539/eer.v5n1p75","title":"Using Simulation to Test the Reliability of Regression Models","year":2015,"lang":"en","type":"article","venue":"Energy and Environment Research","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; National Science Foundation","keywords":"Reliability (semiconductor); Computer science; Range (aeronautics); Regression analysis; Sample size determination; Linear regression; Statistics; Regression; Statistical model; Mathematics; Machine learning; Engineering","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":[0.03192008,0.001734192,0.001117829,0.002033385,0.0006209562,0.001490208,0.001955007,0.001746498,0.002229477],"category_scores_gemma":[0.1394586,0.0006798944,0.001773586,0.001800903,0.001324814,0.001917301,0.00144734,0.002536608,0.0004688491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001082681,"about_ca_system_score_gemma":0.001689762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003124906,"about_ca_topic_score_gemma":0.001633084,"domain_scores_codex":[0.9715354,0.02129854,0.00118167,0.00165973,0.003784183,0.0005405024],"domain_scores_gemma":[0.7836952,0.1866457,0.008409581,0.01384544,0.007057121,0.0003468852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001374329,0.0009529962,0.04362462,0.0007953323,0.001150678,0.0002463914,0.0007020553,0.839439,0.006766677,0.04278941,0.002114835,0.06004367],"study_design_scores_gemma":[0.0001501964,0.001262182,0.004264837,0.0001350958,0.0001519395,0.0001344238,0.0001807837,0.9662729,0.007416468,0.01742576,0.002526605,0.00007886728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2396395,0.0006199346,0.7521917,0.00043534,0.0002638359,0.000741192,0.0006614969,0.001216893,0.004230103],"genre_scores_gemma":[0.7350742,0.0006372049,0.2607947,0.0001852412,0.00007788609,0.00115128,0.0009526077,0.0002356148,0.0008912898],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03192008,"threshold_uncertainty_score":0.1688115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1608722287389324,"score_gpt":0.376096487047994,"score_spread":0.2152242583090615,"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."}}