{"id":"W2507645692","doi":"10.1038/srep31951","title":"Distinguishing autocrine and paracrine signals in hematopoietic stem cell culture using a biofunctional microcavity platform","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Universität Leipzig; Deutsche Forschungsgemeinschaft","keywords":"Paracrine signalling; Autocrine signalling; Haematopoiesis; Stem cell; Cell biology; Admiration; Biology; Cell culture; Psychology; Receptor; Genetics","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":[0.002031042,0.0001648834,0.0002212382,0.0002081681,0.0001552152,0.0002396578,0.0001327668,0.00008685631,0.0001298133],"category_scores_gemma":[0.0002456531,0.0001135343,0.00004978247,0.0004944301,0.0002505707,0.0002155981,0.0001706235,0.0002077115,0.00001861893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001576582,"about_ca_system_score_gemma":0.00006693107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001984498,"about_ca_topic_score_gemma":0.00001092489,"domain_scores_codex":[0.9977214,0.00002548296,0.0005822773,0.0005536136,0.0006403245,0.0004768827],"domain_scores_gemma":[0.9990711,0.0001166797,0.0001021729,0.0004193712,0.00009791616,0.0001927873],"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":[0.000007052794,0.00005838462,0.0312471,0.0003434501,0.00001415656,0.0007320277,0.0005171189,0.0006039219,0.953826,0.00003219289,0.003315423,0.00930315],"study_design_scores_gemma":[0.001749829,0.0001014201,0.02428718,0.002444558,0.00004911342,0.003575822,0.0005888267,0.05938532,0.7893935,0.02313982,0.09338447,0.001900121],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945297,0.0002630031,0.002407152,0.00005686571,0.001658542,0.0001936933,0.000004088546,0.0001248647,0.0007621293],"genre_scores_gemma":[0.9966102,0.000006562667,0.001620763,0.000005358224,0.0000598832,0.00001005735,0.000005985825,0.00002131358,0.001659927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1644325,"threshold_uncertainty_score":0.4629795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0261621163648436,"score_gpt":0.2665884970787071,"score_spread":0.2404263807138635,"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."}}