{"id":"W2132808326","doi":"10.1039/c4bm00299g","title":"Engineering personalized neural tissue by combining induced pluripotent stem cells with fibrin scaffolds","year":2014,"lang":"en","type":"article","venue":"Biomaterials Science","topic":"Pluripotent Stem Cells Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Induced pluripotent stem cell; Human Induced Pluripotent Stem Cells; Tissue engineering; Fibrin; Stem cell; Cell biology; Neural stem cell; Chemistry; Biology; Biomedical engineering; Embryonic stem cell; Medicine; Biochemistry; Immunology; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002684317,0.0004384571,0.000244243,0.0005319536,0.0001208462,0.0003707455,0.0002224113,0.0002938582,0.001124739],"category_scores_gemma":[0.0002112066,0.0001841559,0.0002616325,0.0002863248,0.0001422304,0.0004077064,0.0004184473,0.0002966959,0.0004053715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001774473,"about_ca_system_score_gemma":0.0002057609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003040391,"about_ca_topic_score_gemma":0.0006726874,"domain_scores_codex":[0.9998012,0.00002771834,0.00002211113,0.00003512083,0.00008807458,0.00002573902],"domain_scores_gemma":[0.9999087,0.00002075546,0.00003654785,0.00001208521,0.00001275527,0.00000906137],"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":[0.00004966807,0.00002549761,0.000269574,0.0001531061,0.00001498205,0.0001906825,0.00002876973,0.001583297,0.980886,0.0002979587,0.00008887217,0.01641165],"study_design_scores_gemma":[0.00001798798,0.0004274835,0.001512147,0.00004213903,0.0000434877,0.0006736034,0.00003801227,0.005167457,0.9813967,0.0003156397,0.01034932,0.00001601536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8132196,0.009211935,0.166192,0.0001668979,0.0002012158,0.0004741932,0.0006604164,0.000580001,0.009293703],"genre_scores_gemma":[0.8488552,0.006647462,0.1381791,0.000115986,0.00004617601,0.0002826919,0.0006024042,0.0001173485,0.005153692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001124739,"threshold_uncertainty_score":0.003762603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01179596924314055,"score_gpt":0.2419262598333462,"score_spread":0.2301302905902057,"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."}}