{"id":"W2081906155","doi":"10.1126/science.1068793","title":"Multicolor and Electron Microscopic Imaging of Connexin Trafficking","year":2002,"lang":"en","type":"article","venue":"Science","topic":"Connexins and lens biology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":901,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Diabetes and Digestive and Kidney Diseases; National Center for Research Resources; National Institute of General Medical Sciences; National Institute on Deafness and Other Communication Disorders","keywords":"Vesicle; Electron microscope; Biophysics; Connexin; Fluorescence; Cell biology; Chemistry; Gap junction; Membrane; Nanotechnology; Biology; Materials science; Biochemistry; Intracellular; Optics; Physics","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":[0.0003225629,0.0002493471,0.0001532985,0.0004382152,0.0003438668,0.0003393241,0.0003848449,0.0004836082,0.001974143],"category_scores_gemma":[0.0002447578,0.0002620791,0.0001991731,0.0002184565,0.0003532637,0.0006037237,0.0004601815,0.0007932546,0.0005118218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004778782,"about_ca_system_score_gemma":0.0002417131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009385156,"about_ca_topic_score_gemma":0.001781709,"domain_scores_codex":[0.9998404,0.00001961886,0.000007938371,0.00004276946,0.00005614364,0.00003311651],"domain_scores_gemma":[0.9997988,0.00004380704,0.00002660652,0.0000491138,0.00004358497,0.00003805092],"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":[0.00003650863,0.00001122414,0.0001489951,0.00002653675,0.000005555406,0.000052624,0.00001412646,0.0001434713,0.9953992,0.001148003,0.00007658295,0.00293712],"study_design_scores_gemma":[0.0000238799,0.00009872171,0.008861759,0.00001142292,0.00001667194,0.001996336,0.00005660596,0.007462773,0.9733533,0.0007784661,0.007317746,0.00002227143],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8099729,0.004142927,0.1699239,0.0004298831,0.0001278227,0.00009684919,0.0005569476,0.0006274849,0.01412123],"genre_scores_gemma":[0.8029826,0.001669576,0.1812276,0.000212109,0.00004492808,0.0001570798,0.0003886379,0.0001427694,0.01317473],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001974143,"threshold_uncertainty_score":0.006604135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008470831549116887,"score_gpt":0.2585111466244488,"score_spread":0.2500403150753319,"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."}}