{"id":"W4288066486","doi":"10.1007/s10561-022-10027-3","title":"Optimization of bovine embryonic fibroblast feeder layer prepared by Mitomycin C","year":2022,"lang":"en","type":"article","venue":"Cell and Tissue Banking","topic":"Pluripotent Stem Cells Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Agriculture","funders":"National Key Research and Development Program of China; Graduate Research and Innovation Projects of Jiangsu Province; Jiangsu Agricultural Science and Technology Innovation Fund","keywords":"Mitomycin C; Fibroblast; Molecular biology; clone (Java method); Alkaline phosphatase; Viability assay; Andrology; In vitro; Cell counting; Biology; Staining; Cell; Chemistry; Biochemistry; Gene; Enzyme; Cell cycle; Medicine; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001230904,0.00009008901,0.000101825,0.00003695268,0.0001328932,0.00001589455,0.000128204,0.00004820248,0.0002625128],"category_scores_gemma":[0.000008819527,0.00009600967,0.00002736883,0.00008674717,0.00003306585,0.000002879285,0.0003023755,0.00007135766,0.000001807535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001179347,"about_ca_system_score_gemma":0.00003262502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002862399,"about_ca_topic_score_gemma":0.000003120229,"domain_scores_codex":[0.9992084,0.00006263461,0.000128924,0.0002604423,0.0001620807,0.0001775279],"domain_scores_gemma":[0.9996674,0.000009614175,0.0000670868,0.0001792265,0.00003442089,0.00004222787],"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":[0.00006561411,0.00005511735,0.0003876023,0.00006586964,0.00001498712,0.000002616677,0.0000713869,0.007244075,0.9870952,0.000003782745,0.004418685,0.0005751089],"study_design_scores_gemma":[0.0005988539,0.0004199334,0.0001021629,0.00001183472,0.00001117538,0.00001397689,0.00008372345,0.002729886,0.8939558,0.000007438545,0.1019123,0.0001529695],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98752,0.004826108,0.003226005,0.0001456423,0.00007278959,0.000257929,0.00005152088,0.00001142956,0.003888593],"genre_scores_gemma":[0.9910048,0.0001362125,0.0005938885,0.0000348881,0.000042063,0.00002103502,0.0002567426,0.00001912202,0.007891251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09749361,"threshold_uncertainty_score":0.3915161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007719714871021266,"score_gpt":0.2360267733771596,"score_spread":0.2283070585061384,"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."}}