{"id":"W4382794101","doi":"10.1016/j.celrep.2023.112737","title":"Dissecting the spermatogonial stem cell niche using spatial transcriptomics","year":2023,"lang":"en","type":"article","venue":"Cell Reports","topic":"Sperm and Testicular Function","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Canadian Institutes of Health Research; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Cecil H. and Ida Green Center for Reproductive Biology Sciences; National Institutes of Health","keywords":"Biology; Niche; Stem cell; Cell biology; Stem cell niche; Transcriptome; Ecological niche; Computational biology; Genetics; Gene; Progenitor cell; Gene expression; Ecology","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":[0.000260696,0.000243848,0.0003182874,0.0005016993,0.0002783246,0.0006658442,0.0002740489,0.0002453641,0.0008447128],"category_scores_gemma":[0.0003065966,0.0001882286,0.0003298891,0.0005273331,0.0004288757,0.000393007,0.0003110337,0.0003518976,0.0001694237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003497157,"about_ca_system_score_gemma":0.0005894981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001887994,"about_ca_topic_score_gemma":0.005052727,"domain_scores_codex":[0.9998794,0.00001796078,0.000006527415,0.00003986328,0.00004199437,0.00001427501],"domain_scores_gemma":[0.9998639,0.00006239129,0.00003026812,0.00001293691,0.00001914591,0.00001130408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000622587,0.00002254708,0.008914432,0.0002585924,0.00006328365,0.000072262,0.00009071962,0.01424751,0.9576677,0.002672871,0.0001943208,0.01573355],"study_design_scores_gemma":[0.00002817547,0.0002405394,0.07596951,0.00006059221,0.0001717118,0.0004157107,0.0007438665,0.2745565,0.6280282,0.008905307,0.01078579,0.00009407323],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7535827,0.00193951,0.2369198,0.0002979623,0.00004438067,0.00005412634,0.003439251,0.0006603088,0.003061922],"genre_scores_gemma":[0.8834532,0.001909203,0.1120786,0.0001308955,0.0000237736,0.00006848537,0.001581494,0.0001132949,0.0006410531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001887994,"threshold_uncertainty_score":0.00375396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02857710811854458,"score_gpt":0.2558129342472895,"score_spread":0.2272358261287449,"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."}}