{"id":"W2947843239","doi":"10.1016/j.jneumeth.2019.05.015","title":"An RFID-based activity tracking system to monitor individual rodent behavior in environmental enrichment: Implications for post-stroke cognitive recovery","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Environmental enrichment; Stroke (engine); Psychology; Cognition; Tracking (education); Stroke recovery; Physical medicine and rehabilitation; Neuroscience; Rehabilitation; Medicine","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":[0.001601665,0.0001395012,0.0003646408,0.00057194,0.00008375922,0.00005996318,0.000190867,0.00007184892,0.000009237981],"category_scores_gemma":[0.0006574257,0.0001170699,0.0002384528,0.0002473054,0.00006207508,0.0004154591,0.00002407021,0.0002589494,0.000002379519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00030807,"about_ca_system_score_gemma":0.0001654587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004455705,"about_ca_topic_score_gemma":7.553519e-7,"domain_scores_codex":[0.9982052,0.0003957028,0.0004586538,0.0003104974,0.0003797079,0.0002502177],"domain_scores_gemma":[0.9981205,0.0009674368,0.0003445924,0.000190559,0.0001169042,0.0002599343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003908912,0.000531724,0.1513186,0.00003141577,0.000004942384,0.000005422893,0.0001398752,0.0002264484,0.7743027,0.000002146173,0.000001484261,0.07304432],"study_design_scores_gemma":[0.001300643,0.00414544,0.9247167,0.000109813,0.00009740915,0.0001273324,0.0008710821,0.0005456937,0.0679023,0.000001982757,0.00007819119,0.000103434],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9658332,0.00003265685,0.03128505,0.0003621729,0.001152078,0.001116873,0.0001906712,0.00001031278,0.00001693904],"genre_scores_gemma":[0.9600405,0.000006141864,0.03923907,0.0004692069,0.0001004825,0.00006280284,0.00000302713,0.00001597446,0.00006280771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.773398,"threshold_uncertainty_score":0.4773971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04914504132582392,"score_gpt":0.4035359226988282,"score_spread":0.3543908813730043,"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."}}