{"id":"W4390343095","doi":"10.1002/jex2.131","title":"The diffusion of normal skin wound myofibroblast‐derived microvesicles differs according to matrix composition","year":2023,"lang":"en","type":"article","venue":"Journal of Extracellular Biology","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Centre Hospitalier Universitaire de Québec; Université Laval","keywords":"Microvesicles; Extracellular matrix; Self-healing hydrogels; Myofibroblast; Wound healing; Chemistry; Fibrin; Extracellular vesicles; Type I collagen; Matrix (chemical analysis); Biophysics; Cell biology; Pathology; Biochemistry; Immunology; Biology; Medicine; Polymer chemistry; Fibrosis","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":[0.0007614021,0.0002204667,0.0003265438,0.000183928,0.0002012053,0.00003863521,0.0005762881,0.0002210544,0.00001187166],"category_scores_gemma":[0.0001962684,0.0001669329,0.0003242045,0.0002655989,0.0002366525,0.00001176513,0.0002924787,0.0001968845,0.00002034904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002995231,"about_ca_system_score_gemma":0.0001142616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006264671,"about_ca_topic_score_gemma":0.000005675717,"domain_scores_codex":[0.9980407,0.0002785572,0.0008026726,0.0002642302,0.0001955318,0.0004183005],"domain_scores_gemma":[0.9984468,0.000152389,0.0006060983,0.0003894259,0.0002168801,0.0001884311],"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":[0.0006268389,0.00008231364,0.003669159,0.00003775852,0.000100526,0.00002636974,0.0000728349,0.0003138083,0.991541,0.0001141551,0.0005152317,0.0029],"study_design_scores_gemma":[0.0008844403,0.0008836597,0.005605286,0.0001099641,0.00005729992,0.0001161858,0.0004334386,0.0001642021,0.9886418,0.0002783076,0.002599788,0.0002256563],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871027,0.0035268,0.008207202,0.0003858812,0.0004549534,0.0002522212,0.00002268981,0.00001131325,0.0000362299],"genre_scores_gemma":[0.9971997,0.0005713805,0.001506177,0.00004967117,0.0003887935,0.000006164429,0.00005270755,0.00003590219,0.0001894635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01009703,"threshold_uncertainty_score":0.6807326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007625990983162701,"score_gpt":0.2702259258343123,"score_spread":0.2625999348511496,"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."}}