{"id":"W4206385286","doi":"10.3390/cells11030351","title":"In-Cell Labeling Coupled to Direct Analysis of Extracellular Vesicles in the Conditioned Medium to Study Extracellular Vesicles Secretion with Minimum Sample Processing and Particle Loss","year":2022,"lang":"en","type":"article","venue":"Cells","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Canadian Glycomics Network; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Nanoparticle tracking analysis; Extracellular vesicles; Flow cytometry; Extracellular; Vesicle; Secretion; Cell; Microvesicles; Extracellular vesicle; Cell biology; Chemistry; Cell culture; Biophysics; Biology; Biochemistry; Immunology; Membrane; microRNA","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":[0.001185381,0.0002209339,0.0003375028,0.0002211302,0.0001762432,0.00004940007,0.0003549466,0.00005480844,0.00005713102],"category_scores_gemma":[0.00007517764,0.0001992414,0.00006981203,0.001281272,0.00007706428,0.00001650464,0.0001939891,0.0001453932,0.000002131567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003990192,"about_ca_system_score_gemma":0.0000752292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001100858,"about_ca_topic_score_gemma":0.000187114,"domain_scores_codex":[0.9977294,0.0003923285,0.0004914883,0.0006113047,0.0004209901,0.0003544883],"domain_scores_gemma":[0.9989966,0.0001246053,0.0001658846,0.0005013809,0.00007325327,0.0001383158],"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":[0.0003608816,0.001051178,0.03175649,0.00004043643,0.00009263944,0.00009319758,0.003972189,0.01563018,0.9467826,0.000008895998,0.0000306488,0.0001805917],"study_design_scores_gemma":[0.00221012,0.001226951,0.02353772,0.00002620985,0.000605069,0.000004723554,0.01320476,0.009345463,0.9485641,0.0000641407,0.0006972735,0.0005135344],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946304,0.002593221,0.001487101,0.000214002,0.00003978462,0.0009451029,0.00006519191,0.00001006505,0.00001514559],"genre_scores_gemma":[0.9983814,0.00001921091,0.0009428317,0.0001918309,0.00003508159,0.0002205788,0.00009897111,0.00003304044,0.00007700147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009232569,"threshold_uncertainty_score":0.812483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0103820050478506,"score_gpt":0.2518625823270075,"score_spread":0.2414805772791569,"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."}}