{"id":"W2908276952","doi":"10.3389/fams.2018.00064","title":"Continuous Predictors of Pretest-Posttest Change: Highlighting the Impact of the Regression Artifact","year":2019,"lang":"en","type":"article","venue":"Frontiers in Applied Mathematics and Statistics","topic":"Mental Health Research Topics","field":"Psychology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University; York University","funders":"","keywords":"Regression analysis; Covariate; Regression toward the mean; Regression; Psychology; Statistics; Linear regression; Baseline (sea); Econometrics; Clinical psychology; 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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2402901,0.001290657,0.00151594,0.002976163,0.001129043,0.003500723,0.00286127,0.002040881,0.004216024],"category_scores_gemma":[0.5722362,0.0007923171,0.004494085,0.004871805,0.003653993,0.003802832,0.003707882,0.004939717,0.0008525833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002030884,"about_ca_system_score_gemma":0.003835179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01035011,"about_ca_topic_score_gemma":0.01320997,"domain_scores_codex":[0.781683,0.1797205,0.009868581,0.01013749,0.01747271,0.001117798],"domain_scores_gemma":[0.2461915,0.6877689,0.01992918,0.03039016,0.01521953,0.0005007262],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002536302,0.0005396194,0.4349932,0.007643774,0.006092267,0.001686102,0.02398669,0.01180979,0.002724225,0.0742599,0.01820742,0.4155208],"study_design_scores_gemma":[0.0005295086,0.004729303,0.6301106,0.008900796,0.005726548,0.003121149,0.0104709,0.1187221,0.01321551,0.126218,0.0775964,0.0006591814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.186803,0.01507774,0.7635745,0.0137262,0.002103943,0.001886959,0.001861729,0.001873275,0.01309262],"genre_scores_gemma":[0.824752,0.00156615,0.1652106,0.002327118,0.0003887212,0.001919353,0.000553176,0.0007474694,0.002535447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7597099,"threshold_uncertainty_score":0.9368576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03079845211550845,"score_gpt":0.3476965278225722,"score_spread":0.3168980757070637,"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."}}