{"id":"W13406669","doi":"10.1023/a:1024866504538","title":"Towards predictive models of stem cell fate","year":2003,"lang":"en","type":"article","venue":"Cytotechnology","topic":"Pluripotent Stem Cells Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Massachusetts Institute of Technology; National Science Foundation","keywords":"Stem cell; Cell fate determination; Embryonic stem cell; Computational model; Biology; Computational biology; Computer science; Transcription factor; Cell biology; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007923152,0.0007091616,0.0006775519,0.0005231313,0.0003117244,0.001383995,0.001689629,0.001003061,0.002154972],"category_scores_gemma":[0.002652081,0.0004685033,0.0005296175,0.0004288214,0.001243569,0.001979778,0.0007448366,0.001754542,0.0004771206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001054057,"about_ca_system_score_gemma":0.0007633705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001900038,"about_ca_topic_score_gemma":0.001628157,"domain_scores_codex":[0.9998291,0.00004946487,0.000005819247,0.0000231069,0.00007832106,0.00001413972],"domain_scores_gemma":[0.9989972,0.0006487845,0.0001112864,0.0001015209,0.000102952,0.00003837171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002101241,0.00002465744,0.0002272803,0.00005286415,0.00001382154,0.00003244938,0.00003252706,0.7193722,0.004059231,0.2673209,0.0007612643,0.008081737],"study_design_scores_gemma":[0.000003715424,0.000005562729,0.00003994526,0.000004117014,0.000003654307,0.000005216573,0.000004280071,0.9001265,0.000718292,0.09848793,0.0005967049,0.000004062636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02592248,0.0005071873,0.9613044,0.0009277947,0.0001022842,0.00003550008,0.0002029853,0.0003614563,0.01063591],"genre_scores_gemma":[0.8164419,0.002354096,0.1700942,0.0004540528,0.0002374068,0.0003518655,0.0005294053,0.0002939946,0.009242956],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002154972,"threshold_uncertainty_score":0.007647812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524144184158566,"score_gpt":0.2417649242801429,"score_spread":0.2265234824385573,"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."}}