{"id":"W3203295104","doi":"10.1016/j.bpj.2021.09.018","title":"Vesicle Viewer: Online visualization and analysis of small-angle scattering from lipid vesicles","year":2021,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Lipid Membrane Structure and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Vesicle; Visualization; Computer science; Python (programming language); Lipid bilayer; Small-angle scattering; Neutron scattering; Bilayer; Software; Lipid vesicle; Scattering; The Internet; Nanotechnology; Materials science; Data mining; Chemistry; Physics; World Wide Web; Optics; Membrane; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004348155,0.00009500238,0.0002102321,0.0000453885,0.00005970737,0.00003364446,0.00007731884,0.00006486783,0.00003570173],"category_scores_gemma":[0.00002574133,0.00008203572,0.0001500438,0.0002164319,0.00004958788,0.000005518104,0.00007114765,0.00006678192,7.303784e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005280334,"about_ca_system_score_gemma":0.00003389858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001264627,"about_ca_topic_score_gemma":0.00001914246,"domain_scores_codex":[0.9993323,0.00005471211,0.0002076241,0.0001879218,0.0001049151,0.000112532],"domain_scores_gemma":[0.9995405,0.000009885459,0.0001039177,0.0001493519,0.0001127513,0.00008358737],"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":[0.00002325555,0.0001242056,0.00318292,0.000006444462,0.0002825955,0.00000616902,0.00005371773,0.00001524564,0.9879856,0.00001737208,0.00002549147,0.008276992],"study_design_scores_gemma":[0.0002792764,0.00007294088,0.07335392,0.00001217083,0.0005399532,0.00001208821,0.00008048391,0.0002549408,0.9247098,0.00000781633,0.0005812733,0.00009531954],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985209,0.0001046091,0.001083516,0.00006715493,0.0001141726,0.0000223433,0.00007091259,0.000003627254,0.00001273418],"genre_scores_gemma":[0.9977937,0.0001894682,0.0007687319,0.0001540618,0.000765226,6.650081e-7,0.0002863639,0.00001018119,0.00003154752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07017099,"threshold_uncertainty_score":0.3345319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01435007914632509,"score_gpt":0.2722064301430145,"score_spread":0.2578563509966894,"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."}}