{"id":"W2127190444","doi":"10.1371/journal.pone.0010854","title":"MicroRNA Networks in Mouse Lung Organogenesis","year":2010,"lang":"en","type":"article","venue":"PLoS ONE","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research","funders":"National Institutes of Health; International Society for Heart and Lung Transplantation; Mayo Clinic","keywords":"Organogenesis; microRNA; Biology; Lung; Computational biology; Cell biology; Bioinformatics; Medicine; Genetics; Internal medicine; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002473699,0.0002970704,0.000222205,0.0008805026,0.0001381255,0.0003103036,0.0001422965,0.0001634864,0.000493383],"category_scores_gemma":[0.0002550631,0.0002389517,0.0002553268,0.0003719178,0.0002299645,0.0001701702,0.0002305533,0.0002708719,0.0002672519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004117262,"about_ca_system_score_gemma":0.0002213915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004305996,"about_ca_topic_score_gemma":0.000575263,"domain_scores_codex":[0.9997625,0.00003697664,0.00001518112,0.00009306011,0.00006609929,0.00002622054],"domain_scores_gemma":[0.9997185,0.00005761005,0.0001446548,0.0000167475,0.0000316242,0.00003088733],"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":[0.000225412,0.0000136598,0.006586918,0.0000840586,0.00003074415,0.00008220714,0.00002929509,0.001007631,0.9866627,0.0004036412,0.00009683154,0.004777098],"study_design_scores_gemma":[0.00003995053,0.0005385609,0.2720553,0.00005396797,0.0002073847,0.00126156,0.00009743173,0.01718349,0.6985041,0.001785664,0.008237601,0.00003491113],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774426,0.00337319,0.01593634,0.00006904965,0.00000877861,0.00003675953,0.00153725,0.0002999077,0.001296167],"genre_scores_gemma":[0.9854974,0.001122949,0.01024625,0.0000538891,0.000004912101,0.0001328904,0.00195033,0.00004185348,0.0009494913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008805026,"threshold_uncertainty_score":0.002987266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01025600884043929,"score_gpt":0.2088259664881302,"score_spread":0.1985699576476909,"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."}}