{"id":"W2299231398","doi":"10.1016/j.celrep.2016.02.078","title":"Signaling Networks among Stem Cell Precursors, Transit-Amplifying Progenitors, and their Niche in Developing Hair Follicles","year":2016,"lang":"en","type":"article","venue":"Cell Reports","topic":"Hair Growth and Disorders","field":"Medicine","cited_by":202,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of General Medical Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; Fondation pour la Recherche Médicale; Icahn School of Medicine at Mount Sinai; New York State Department of Health; Irma T. Hirschl Trust; National Cancer Institute; National Institutes of Health","keywords":"Cell biology; Hair follicle; Biology; Crosstalk; Niche; Morphogenesis; Stem cell; Progenitor cell; Progenitor; Signal transduction; Cell fate determination; Transcriptome; Cell signaling; Transcription factor; Genetics; Gene; Gene expression; Biochemistry","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":[0.0004480578,0.0002530801,0.0003722192,0.0001247815,0.00009242932,0.00002951817,0.00005481553,0.0001892128,0.00001274254],"category_scores_gemma":[0.0000259524,0.0001698088,0.00009387128,0.000221903,0.00008176293,0.0001400241,0.00003537149,0.0001717024,0.000001775621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006756456,"about_ca_system_score_gemma":0.0001757247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005628199,"about_ca_topic_score_gemma":0.00005204523,"domain_scores_codex":[0.9982268,0.00005621065,0.0005655274,0.0004966611,0.0001701931,0.0004846235],"domain_scores_gemma":[0.999116,0.000131111,0.0001867816,0.0002815185,0.00005543619,0.0002291423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001006058,0.0001210727,0.9240763,0.0004376287,0.00003579579,0.0009379648,0.002629806,0.0001053717,0.03387583,0.00001049967,0.0002342164,0.03743491],"study_design_scores_gemma":[0.006954282,0.0004658914,0.1232458,0.004316384,0.0002390799,0.000935495,0.006936181,0.001551643,0.8393672,0.0008830403,0.01307834,0.002026621],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826449,0.003222149,0.01124247,0.0001997773,0.0001838988,0.0006482779,8.266207e-7,0.0001076077,0.001750102],"genre_scores_gemma":[0.9984321,0.0001845872,0.0006136047,0.0001256882,0.0001110599,0.00004505556,0.000007211052,0.00004710944,0.0004335862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8054914,"threshold_uncertainty_score":0.6924601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01381970024213913,"score_gpt":0.2166863574154626,"score_spread":0.2028666571733235,"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."}}