{"id":"W1975494033","doi":"10.1177/0013164413487738","title":"False Positives in Multiple Regression","year":2013,"lang":"en","type":"article","venue":"Educational and Psychological Measurement","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Type I and type II errors; Statistics; Regression; False positive paradox; Regression analysis; Econometrics; Observational error; Regression diagnostic; Nominal level; Inflation (cosmology); Computer science; Linear regression; False positives and false negatives; Mathematics; Polynomial regression; Confidence interval","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003928839,0.00009539343,0.000130848,0.00003182792,0.00005754854,0.00001594623,0.0000551281,0.00004780065,0.0004158877],"category_scores_gemma":[0.001398457,0.00006095699,0.00002124748,0.00005725665,0.00005635683,0.00006018958,0.00001666317,0.0001071893,0.00002443259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003225187,"about_ca_system_score_gemma":0.000009238373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001078703,"about_ca_topic_score_gemma":0.000004853232,"domain_scores_codex":[0.999048,0.000122609,0.0002004043,0.0002518154,0.0002283687,0.0001488262],"domain_scores_gemma":[0.9990852,0.0005633185,0.00004286361,0.0001078371,0.0001035328,0.00009728966],"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":[0.0001147826,0.003868335,0.01513179,0.00007721171,0.00002512522,0.000003341016,0.0007792232,0.000004551204,0.02063109,0.7100284,0.01132927,0.2380069],"study_design_scores_gemma":[0.0002612132,0.0000704745,0.1881197,0.00005502917,0.000002491864,0.000003283601,0.00006265477,0.00005150238,0.0001012813,0.8109105,0.000278363,0.00008343883],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8638424,0.0006613889,0.1163965,0.0107698,0.0003743314,0.0007774924,0.000008923082,0.00003505592,0.007134133],"genre_scores_gemma":[0.8089048,0.00001930528,0.1904628,0.0002370197,0.00005855909,0.0001403084,0.000001673928,0.000004450955,0.000171165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2379235,"threshold_uncertainty_score":0.4553679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.450798048209222,"score_gpt":0.4850311437518074,"score_spread":0.03423309554258541,"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."}}