{"id":"W3031611299","doi":"10.1101/2020.05.25.114421","title":"Distinguishing within- from between-individual effects: How to use the within-individual centering method for quadratic patterns","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Animal Ecology and Behavior Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Quadratic equation; Variable (mathematics); Inference; Range (aeronautics); Structural equation modeling; Mathematics; Applied mathematics; Process (computing); Population; Statistical physics; Econometrics; Computer science; Statistics; Mathematical analysis; Physics; Artificial intelligence; Geometry","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":[0.04073417,0.0007784794,0.001956083,0.00270845,0.001155384,0.002069814,0.00393885,0.001908737,0.005085429],"category_scores_gemma":[0.1757194,0.0007816673,0.002892157,0.002391479,0.003110391,0.00304101,0.002708822,0.004250965,0.00114771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001281769,"about_ca_system_score_gemma":0.002198681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007025002,"about_ca_topic_score_gemma":0.005986453,"domain_scores_codex":[0.9794511,0.01428127,0.001124212,0.002436982,0.002244398,0.0004621719],"domain_scores_gemma":[0.7855977,0.1831217,0.005861032,0.01476552,0.009410067,0.001244012],"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":[0.0005620345,0.0003924978,0.05650338,0.0007272847,0.001592826,0.001034352,0.002564277,0.1767828,0.01529128,0.1446194,0.009200016,0.5907297],"study_design_scores_gemma":[0.00006027121,0.0001467533,0.01177168,0.0001089477,0.0001834087,0.0002710558,0.0002309149,0.8557425,0.006249953,0.1186575,0.006413796,0.0001632712],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005865148,0.0000471181,0.9931298,0.0001575356,0.0000350859,0.00007497908,0.00003634267,0.0002999129,0.0003540454],"genre_scores_gemma":[0.1630836,0.00009623846,0.8344249,0.0002527713,0.00009455848,0.0003903343,0.0001826445,0.0005590564,0.0009158863],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04073417,"threshold_uncertainty_score":0.2154255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04329797275653286,"score_gpt":0.2656678076128779,"score_spread":0.222369834856345,"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."}}