{"id":"W4301309049","doi":"10.17615/eg0z-fb92","title":"Social Media and the Practicing Hematologist: Twitter 101 for the Busy Healthcare Provider","year":2020,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Aurora Research Institute; American Society for Blood and Marrow Transplantation","keywords":"Hematologist; Social media; Health care; Internet privacy; Computer science; World Wide Web; Medicine; Political science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002552469,0.000391135,0.000320591,0.001216228,0.008489071,0.01222075,0.0005401733,0.003555338,0.01995942],"category_scores_gemma":[0.01646974,0.0002978718,0.0002845418,0.001491492,0.002434311,0.01106173,0.004378492,0.003392454,0.004687203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001839791,"about_ca_system_score_gemma":0.002681686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002265492,"about_ca_topic_score_gemma":0.006886986,"domain_scores_codex":[0.9968359,0.00193597,0.000155643,0.0001325187,0.0006097356,0.0003302749],"domain_scores_gemma":[0.9873281,0.007164396,0.00129999,0.0003062187,0.0009519325,0.002949311],"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":[0.0001692626,0.0001795896,0.02053082,0.0009691927,0.00004041674,0.002299381,0.06537642,0.0000984023,0.001768596,0.02278118,0.5776383,0.3081484],"study_design_scores_gemma":[0.0000130654,0.00009717298,0.005943527,0.001161318,0.00002472421,0.001482209,0.06919918,0.000216626,0.0005597921,0.004998493,0.9162276,0.00007622758],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.04801111,0.01722753,0.002074209,0.8027003,0.006294604,0.0001016046,0.0004151296,0.0004734895,0.122702],"genre_scores_gemma":[0.6133384,0.04449354,0.009777131,0.1683048,0.01421451,0.0002596164,0.000663323,0.0007786341,0.1481701],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01995942,"threshold_uncertainty_score":0.06677091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.266002312291512,"score_gpt":0.4082521099897671,"score_spread":0.1422497976982551,"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."}}