{"id":"W1998049624","doi":"10.3389/fpsyg.2014.01548","title":"On the efficacy of procedures to normalize Ex-Gaussian distributions","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Outlier; Normality; Transformation (genetics); Gaussian; Normal distribution; Parametric statistics; Skewness; Mathematics; Percentile; Statistics; Data transformation; Exponential family; Power transform; Applied mathematics; Econometrics; Computer science; Data mining; Physics; Discrete mathematics","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":[0.03040309,0.001505053,0.0008161422,0.002205164,0.001234952,0.002154751,0.001539313,0.001345424,0.00303558],"category_scores_gemma":[0.1263567,0.00045886,0.001364279,0.002789394,0.003049797,0.002653806,0.00194536,0.002377603,0.00138884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007763914,"about_ca_system_score_gemma":0.001576305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001542909,"about_ca_topic_score_gemma":0.001465578,"domain_scores_codex":[0.9849705,0.008520115,0.0009459435,0.001819698,0.003463757,0.000280182],"domain_scores_gemma":[0.9240329,0.05763803,0.003938995,0.007325315,0.006760536,0.0003042646],"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":[0.00108605,0.0004248592,0.009094578,0.001325041,0.0005274471,0.0002504845,0.002576904,0.03355513,0.04318504,0.07190562,0.004149926,0.831919],"study_design_scores_gemma":[0.0005009536,0.002494874,0.05836596,0.001288526,0.000908878,0.002303062,0.002468552,0.4335234,0.2305544,0.2092802,0.05750614,0.0008051184],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02935027,0.0007093886,0.966234,0.000271451,0.0001199867,0.0002677114,0.0001385154,0.00100934,0.001899293],"genre_scores_gemma":[0.219072,0.00139773,0.7751696,0.0003090876,0.0001121406,0.001099741,0.000533368,0.001097109,0.001209277],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03040309,"threshold_uncertainty_score":0.1607888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05730943982861437,"score_gpt":0.3476683201539722,"score_spread":0.2903588803253578,"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."}}