{"id":"W4400473598","doi":"10.1002/jev2.12475","title":"Connecting through ISEV's developing social media landscape","year":2024,"lang":"en","type":"editorial","venue":"Journal of Extracellular Vesicles","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centros de Pesquisa, Inovação e Difusão, Fundação Amazônia Paraense de Amparo à Pesquisa; Biotechnology and Biological Sciences Research Council","keywords":"Social media; Social media optimization; Promotion (chess); Public relations; Sociology; Media studies; Internet privacy; Political science; World Wide Web; Advertising; Business; Computer science; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004232968,0.0005988788,0.0002523792,0.001865711,0.003713039,0.01978775,0.001276753,0.004299439,0.01770558],"category_scores_gemma":[0.009077147,0.0003479072,0.0004221397,0.001014654,0.002781483,0.01199104,0.007560701,0.004324902,0.007663064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004228177,"about_ca_system_score_gemma":0.003649637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003869788,"about_ca_topic_score_gemma":0.01115982,"domain_scores_codex":[0.9967129,0.001073468,0.0001373926,0.0002878259,0.00140652,0.0003818717],"domain_scores_gemma":[0.9948151,0.002135222,0.0003140983,0.0002656174,0.001213811,0.001256153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000470918,0.00003756667,0.001134104,0.0004075711,0.00001353973,0.0008117679,0.005781593,0.0001661897,0.002037501,0.1027005,0.7413395,0.1455231],"study_design_scores_gemma":[0.000001747615,0.000006612674,0.0003200838,0.00009745838,0.000001995059,0.0001109485,0.0006898373,0.00006524241,0.0001706892,0.001565819,0.9969614,0.00000822242],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"editorial","genre_scores_codex":[0.01437485,0.02658733,0.0110017,0.199513,0.03745922,0.0001944135,0.000629401,0.001391831,0.7088482],"genre_scores_gemma":[0.1560992,0.04382139,0.01671735,0.06325139,0.0235252,0.0003913389,0.002101798,0.002348308,0.6917441],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.01978775,"threshold_uncertainty_score":0.0592311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08732204432052763,"score_gpt":0.3887131924016287,"score_spread":0.3013911480811011,"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."}}