{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006071437,0.00017722,0.0001405896,0.0002158899,0.0002688806,0.00008510789,0.0002273503,0.000169593,0.0005613939],"category_scores_gemma":[0.0003208446,0.0001292306,0.0000979748,0.0002675299,0.0001339783,0.00002773486,0.0000844163,0.0001966577,0.00004258409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001055062,"about_ca_system_score_gemma":0.0001059538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004531333,"about_ca_topic_score_gemma":0.00001886614,"domain_scores_codex":[0.9974628,0.0003800983,0.0002340553,0.0005209877,0.0008465546,0.0005554663],"domain_scores_gemma":[0.9990022,0.00006713269,0.00003477539,0.0003169709,0.0003913196,0.0001876374],"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":[0.0001497441,0.00002534945,0.0004118031,0.0000161083,0.00001972954,0.000004838258,0.00002168719,0.001139576,0.9941841,0.0001380486,0.000897831,0.002991221],"study_design_scores_gemma":[0.0009498911,0.0002269811,0.0008243612,0.00001504174,0.000005700167,0.00001881161,0.00002457631,0.01542553,0.9432666,0.00001249408,0.03904011,0.0001898971],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988687,0.0005581969,0.008900789,0.001011703,0.0002744571,0.0003769349,0.00002314449,0.00002951276,0.0001382959],"genre_scores_gemma":[0.9860767,0.0001315419,0.0002879662,0.00003138473,0.0005079185,0.00004263103,0.0001267973,0.00004070441,0.01275441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05091746,"threshold_uncertainty_score":0.614687,"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."}}