{"id":"W2005354201","doi":"10.1111/j.1552-6569.2007.00180.x","title":"Functional Imaging of Stroke Recovery: An Ecological Review from a Neural Network Perspective with an Emphasis on Motor Systems","year":2008,"lang":"en","type":"review","venue":"Journal of Neuroimaging","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Perspective (graphical); Medicine; Neuroscience; Motor function; Stroke (engine); Functional connectivity; Neuroplasticity; Structural plasticity; Stroke recovery; Rehabilitation; Physical medicine and rehabilitation; Artificial intelligence; Computer science; Psychology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004833761,0.0005343366,0.003264829,0.0005069402,0.0001135254,0.00005371319,0.0002518255,0.0001261259,0.00009854934],"category_scores_gemma":[0.0005228362,0.0003380044,0.001285562,0.0003940135,0.0001601113,0.0004408927,0.00003538038,0.001309768,0.000006204237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004860105,"about_ca_system_score_gemma":0.0007606276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002922718,"about_ca_topic_score_gemma":0.000001158758,"domain_scores_codex":[0.9956763,0.0009534389,0.001571579,0.0005459353,0.0009019806,0.0003507962],"domain_scores_gemma":[0.9950426,0.001101165,0.002219867,0.0004696573,0.0008018332,0.0003648539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003663773,0.004026907,0.01042038,0.03360357,0.003244222,0.005928005,0.0002652976,0.001817745,0.00004031001,0.00008937205,0.01731937,0.9195811],"study_design_scores_gemma":[0.004266213,0.01776323,0.03871127,0.2719536,0.008640299,0.04100565,0.0007630599,0.001187091,8.145407e-7,0.00003852756,0.6143771,0.001293209],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004844457,0.9917888,0.00006526979,0.0003678949,0.001561217,0.0009540603,0.0000866712,0.00003076937,0.0003008518],"genre_scores_gemma":[0.000858281,0.9951394,0.0008239519,0.0006467236,0.002294895,0.00001845169,0.00004147329,0.00008734331,0.00008951769],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9182878,"threshold_uncertainty_score":0.9999072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05900120173454514,"score_gpt":0.3396990842047103,"score_spread":0.2806978824701651,"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."}}