{"id":"W2290471774","doi":"10.3109/19396368.2015.1062578","title":"Quantitative large scale gene expression profiling from human stem cell culture micro samples using multiplex pre-amplification","year":2015,"lang":"en","type":"article","venue":"Systems Biology in Reproductive Medicine","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Bio-Rad (Canada); Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute","funders":"Canadian Institutes of Health Research; Agence Nationale pour la Gestion des Déchets Radioactifs","keywords":"Induced pluripotent stem cell; Biology; Reprogramming; Multiplex; Gene expression profiling; Stem cell; Computational biology; Embryoid body; Embryonic stem cell; Gene expression; Gene; Genetics","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":[0.0009487535,0.000275495,0.0004136629,0.000100747,0.0001359555,0.000008344969,0.0002827078,0.0004169308,0.00000363289],"category_scores_gemma":[0.0001360223,0.0002137157,0.00005367161,0.0001843651,0.0003100568,0.000007251268,0.0001553402,0.0002119258,0.000003979442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006696236,"about_ca_system_score_gemma":0.00006020683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007441695,"about_ca_topic_score_gemma":0.0000431923,"domain_scores_codex":[0.9973139,0.000502512,0.0005657026,0.001187519,0.0001049165,0.0003254476],"domain_scores_gemma":[0.9982715,0.00002205188,0.0003827539,0.0008891816,0.0003335125,0.0001009491],"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":[0.0001004223,0.0001068244,0.03203975,0.00002112418,0.00002763716,0.000001329782,0.0007679955,0.00006267954,0.9659677,0.000351868,0.0005195546,0.00003316132],"study_design_scores_gemma":[0.001008203,0.0005528731,0.001508732,0.00008714182,0.00002881895,0.00001605964,0.003723242,0.000157286,0.9861091,0.0005080525,0.006031262,0.0002691826],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.895746,0.00703137,0.09531316,0.00009433413,0.0002609931,0.001139799,0.0001847302,0.00004189509,0.0001877107],"genre_scores_gemma":[0.9682019,0.00008540613,0.0279553,0.00005251519,0.0006698021,0.0002654401,0.002521916,0.00003129135,0.0002163851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07245594,"threshold_uncertainty_score":0.8715072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07367053345636211,"score_gpt":0.3637302355601975,"score_spread":0.2900597021038354,"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."}}