{"id":"W3106447111","doi":"10.1007/s12015-020-10064-z","title":"Characterization and Functional Assessment of Endothelial Progenitor Cells in Ischemic Stroke Patients","year":2020,"lang":"en","type":"article","venue":"Stem Cell Reviews and Reports","topic":"Angiogenesis and VEGF in Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; Mechanobiology Institute, Singapore; University of Waterloo; National Research Foundation Singapore; National Research Foundation","keywords":"Progenitor cell; Medicine; Stroke (engine); Ischemic stroke; Stem cell; Endothelial progenitor cell; Internal medicine; Neuroscience; Cardiology; Ischemia; Biology; Cell biology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001081757,0.00008495351,0.000169213,0.00001120514,0.00001757764,0.000006520671,0.00001675242,0.00005301793,0.00001028591],"category_scores_gemma":[0.000002654153,0.00006670065,0.00004805041,0.00002966083,0.00002009384,0.000003462969,0.00003920855,0.00002793843,3.122373e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004320381,"about_ca_system_score_gemma":0.00003276084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001802218,"about_ca_topic_score_gemma":7.620764e-7,"domain_scores_codex":[0.9992793,0.00002787339,0.0003240959,0.0002246403,0.00007184873,0.00007221768],"domain_scores_gemma":[0.9996085,0.000002070054,0.0002263216,0.00008318914,0.00003086451,0.00004906777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008417423,0.00002725944,0.1201676,0.0001660769,0.000006093137,0.000001640317,0.00001540129,6.520426e-7,0.8684956,6.366539e-7,0.0002151532,0.01089544],"study_design_scores_gemma":[0.0003004866,0.0001646423,0.03862439,0.00004203664,0.00002217035,0.000005418217,0.00001327073,0.00001798603,0.5691555,2.622452e-7,0.3915332,0.0001206058],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939407,0.004869421,0.0003236493,0.00001690533,0.0001220934,0.0003346939,0.00003156557,0.000001551068,0.0003594902],"genre_scores_gemma":[0.9919114,0.007336829,0.0001324676,0.00008917573,0.0001241673,0.0000282206,0.0001004999,0.000008089221,0.0002692211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3913181,"threshold_uncertainty_score":0.2719974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446628038360714,"score_gpt":0.2420293425451214,"score_spread":0.2275630621615143,"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."}}