{"id":"W2105372361","doi":"10.1038/msb.2009.49","title":"Cell–cell interaction networks regulate blood stem and progenitor cell fate","year":2009,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Hematopoietic Stem Cell Transplantation","field":"Medicine","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre; Heart and Stroke Foundation; University Health Network; Aptose Biosciences (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Stem Cell Network; John Simon Guggenheim Memorial Foundation","keywords":"Biology; Cell biology; Cell fate determination; Progenitor cell; Stem cell; Cell; In silico; Intracellular; Multicellular organism; Haematopoiesis; Cell type; Cellular differentiation; Cell signaling; Blood cell; Signal transduction; Immunology; Transcription factor; 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":[0.0002286056,0.0003244439,0.0003164957,0.0002277198,0.0003172948,0.0007707304,0.0003696109,0.0004494174,0.0006374762],"category_scores_gemma":[0.001042031,0.0002999459,0.0002686444,0.0002432618,0.0006544383,0.00078564,0.0002628088,0.0003592361,0.0002072559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007160106,"about_ca_system_score_gemma":0.0005659431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001210357,"about_ca_topic_score_gemma":0.001080635,"domain_scores_codex":[0.9998149,0.00004973416,0.000009516404,0.00004754841,0.00005310275,0.00002517203],"domain_scores_gemma":[0.9996866,0.0001684218,0.00007654992,0.00002268583,0.00002789042,0.00001787467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001064375,0.00006003136,0.003505187,0.00007608974,0.00003860739,0.0001585379,0.00008270663,0.5882784,0.3740188,0.02394914,0.0002362318,0.009489912],"study_design_scores_gemma":[0.00002087273,0.00004955164,0.002242571,0.000004901539,0.00002731792,0.00006673411,0.00003374494,0.9317661,0.05515262,0.009052284,0.00156543,0.00001786077],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8383664,0.0006987661,0.1555318,0.0003165368,0.00003224028,0.0000282754,0.0001579468,0.0002805944,0.004587402],"genre_scores_gemma":[0.9940203,0.0003186129,0.004981872,0.00002017655,0.000004554392,0.0000213092,0.00004416797,0.00001577094,0.0005732664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001210357,"threshold_uncertainty_score":0.005195081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008634923532160018,"score_gpt":0.2377507861391323,"score_spread":0.2291158626069723,"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."}}