{"id":"W4225428236","doi":"10.51224/srxiv.152","title":"Action Planning Makes Physical Activity More Automatic, Only If it Is Autonomously Regulated","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Action (physics); Computer science; Process management; Human–computer interaction; Business; Physics","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":[0.0006654305,0.0005001563,0.0003362986,0.0004060614,0.0003681031,0.001666748,0.0004088217,0.0006894522,0.007975264],"category_scores_gemma":[0.003285068,0.0003941735,0.0004958979,0.0004307273,0.0009818596,0.001011348,0.001005094,0.001128132,0.002293706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003499602,"about_ca_system_score_gemma":0.001162341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003208555,"about_ca_topic_score_gemma":0.001636636,"domain_scores_codex":[0.9994185,0.0001248533,0.00002394819,0.0002223144,0.0001440284,0.0000663825],"domain_scores_gemma":[0.9987452,0.0004876029,0.0001740203,0.0003138999,0.0001661345,0.0001131623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008320046,0.001056577,0.02671791,0.0006041729,0.0003893519,0.0004607008,0.001273962,0.03609215,0.1453553,0.2520266,0.01852534,0.5166659],"study_design_scores_gemma":[0.0003057108,0.0007870669,0.1316613,0.0001642746,0.0002164676,0.0007316329,0.0006386843,0.1864314,0.05207769,0.5764728,0.05037797,0.0001350536],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2327574,0.0008278663,0.5624283,0.004236161,0.00076575,0.0001568803,0.001193371,0.003563523,0.1940707],"genre_scores_gemma":[0.8853655,0.0004989767,0.08691853,0.0004355451,0.0002041367,0.0001396557,0.0009906604,0.0005980261,0.02484896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007975264,"threshold_uncertainty_score":0.02667987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04288600930732302,"score_gpt":0.3621485015194519,"score_spread":0.3192624922121289,"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."}}