{"id":"W2768925282","doi":"10.1038/s41598-017-17037-2","title":"Imaging viscosity of intragranular mucin matrix in cystic fibrosis cells","year":2017,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Cystic Fibrosis Research Advances","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Cystic Fibrosis Canada; McGill University; National Science Foundation","keywords":"Mucin; Cystic fibrosis; Mucus; Fluorescence microscope; Pathology; Population; Rheology; Microscopy; Viscosity; Granule (geology); Pathogenesis; Chemistry; Cell biology; Medicine; Biophysics; Materials science; Biology; Fluorescence; Physics; Internal medicine; Composite material; Optics","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":[0.0002083025,0.0001563127,0.0001640465,0.0004108998,0.0001779802,0.0002979147,0.0001756928,0.0004342907,0.000536427],"category_scores_gemma":[0.0002253964,0.0001513093,0.0001247208,0.0001925643,0.0001934392,0.0004405013,0.0003044661,0.0004926109,0.0001430687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002457249,"about_ca_system_score_gemma":0.000131992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005577488,"about_ca_topic_score_gemma":0.0006697059,"domain_scores_codex":[0.9999287,0.00001104869,0.000005251862,0.00001699748,0.00002544839,0.00001255887],"domain_scores_gemma":[0.9998561,0.00004098477,0.00003826125,0.00001274386,0.00002271015,0.00002913245],"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":[0.00001882011,0.000003646117,0.0003455739,0.0000159007,0.000001612191,0.00002683454,0.00004232566,0.0000400799,0.9983659,0.00004567701,0.00001902647,0.001074573],"study_design_scores_gemma":[0.00001423187,0.0001706149,0.0256113,0.00002105362,0.00002296348,0.0005409719,0.0001836768,0.008942114,0.9621459,0.0002245272,0.002102277,0.00002052742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9741381,0.001865179,0.02243988,0.000186269,0.00001940162,0.00002443916,0.0002103297,0.0001254504,0.0009909671],"genre_scores_gemma":[0.9622656,0.002192175,0.03331466,0.0001324484,0.00002686141,0.00008133343,0.0002151305,0.00005483691,0.001716972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005577488,"threshold_uncertainty_score":0.001794577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01115366893474379,"score_gpt":0.3167286797712507,"score_spread":0.3055750108365069,"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."}}