{"id":"W2751674174","doi":"10.1126/sciadv.1700521","title":"Functional vascularized lung grafts for lung bioengineering","year":2017,"lang":"en","type":"article","venue":"Science Advances","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Research Resources; National Institutes of Health; National Cancer Institute; National Heart, Lung, and Blood Institute; Weill Cornell Medical College; National Institute of Biomedical Imaging and Bioengineering; York University","keywords":"Lung; Regeneration (biology); Epithelium; Medicine; Pathology; Biology; Cell biology; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003709259,0.0001114778,0.0001860078,0.0001223709,0.0006665676,0.00005504668,0.0001861736,0.00002542625,0.00002158004],"category_scores_gemma":[0.0005503998,0.00008014824,0.00006394269,0.0001321559,0.0004579035,0.000412576,0.00003470042,0.00008695555,0.000003210945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005617321,"about_ca_system_score_gemma":0.00009196123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003912929,"about_ca_topic_score_gemma":0.000001342374,"domain_scores_codex":[0.9989707,0.000002574787,0.0001169455,0.0002840295,0.000337315,0.0002884095],"domain_scores_gemma":[0.9992864,0.00002897474,0.00005359302,0.000352619,0.0001334808,0.000144892],"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":[0.00009364611,0.00006734135,0.01290661,0.0004448837,0.00008276024,0.00002558898,0.0002390572,0.0096541,0.9319345,0.005316162,0.001316824,0.03791857],"study_design_scores_gemma":[0.009568217,0.0006624941,0.2187644,0.001086236,0.0003301571,0.000216042,0.0002973184,0.2171702,0.4103535,0.0003105215,0.1402962,0.0009448336],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3001527,0.03142056,0.6567096,0.003713451,0.00611904,0.0008499745,0.000008807468,0.0002456983,0.0007802406],"genre_scores_gemma":[0.9746678,0.00005880638,0.01909621,0.00002864022,0.0007150382,0.00005226485,0.000006370181,0.00001347877,0.00536139],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6745151,"threshold_uncertainty_score":0.5126766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01956197335200473,"score_gpt":0.315675248011035,"score_spread":0.2961132746590303,"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."}}