{"id":"W2540916512","doi":"10.4103/1673-5374.193229","title":"Engineering personalized neural tissue using functionalized transcription factors","year":2016,"lang":"en","type":"article","venue":"Neural Regeneration Research","topic":"Pluripotent Stem Cells Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Collaboration On Repair Discoveries; University of Victoria","funders":"","keywords":"Central nervous system; Neuroscience; Multiple sclerosis; Medicine; Transplantation; Nervous system; Spinal cord injury; Neuroregeneration; Neural stem cell; Disease; Spinal cord; Stem cell; Biology; Immunology; Pathology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002121852,0.0003717499,0.0002277054,0.0003362218,0.0001485113,0.0005845309,0.0002929404,0.0006439931,0.003492785],"category_scores_gemma":[0.0002866108,0.0002091807,0.0004343104,0.0002498802,0.0002329359,0.0004914871,0.000310213,0.000695977,0.001271071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004611392,"about_ca_system_score_gemma":0.0002123603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005350064,"about_ca_topic_score_gemma":0.001039943,"domain_scores_codex":[0.999861,0.00001342414,0.000008814282,0.00003969373,0.0000477383,0.00002921149],"domain_scores_gemma":[0.9999183,0.00002047726,0.00002617203,0.000008556893,0.00001564584,0.00001083165],"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":[0.00004830122,0.00003590839,0.0001718913,0.0003626617,0.00002002696,0.0002403353,0.00006645835,0.001762587,0.9727758,0.003003443,0.001084002,0.02042859],"study_design_scores_gemma":[0.00003269252,0.0002925804,0.001019027,0.00009909327,0.00005419775,0.0004771777,0.00008849872,0.008246334,0.9334717,0.001347234,0.05482237,0.00004909507],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6195278,0.0214155,0.2888105,0.00167415,0.001656441,0.000625472,0.002273483,0.002250528,0.06176622],"genre_scores_gemma":[0.8776795,0.0111826,0.08547103,0.0007207668,0.0001070281,0.0004882499,0.00104749,0.0003495557,0.02295385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003492785,"threshold_uncertainty_score":0.01168448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08758134980051019,"score_gpt":0.3493198510160497,"score_spread":0.2617385012155395,"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."}}