{"id":"W4385654927","doi":"10.3390/informatics10030065","title":"Exploring How Healthcare Organizations Use Twitter: A Discourse Analysis","year":2023,"lang":"en","type":"article","venue":"Informatics","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; Vector Institute; York University; Alliance de recherche numérique du Canada; Lakehead University","keywords":"Popularity; Social media; Health care; Reputation; Public relations; Content analysis; Health literacy; Internet privacy; Psychology; Business; World Wide Web; Political science; Computer science; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00919101,0.000515546,0.0004111724,0.004425726,0.004420136,0.00581181,0.0007494536,0.001447217,0.002120245],"category_scores_gemma":[0.02321702,0.0002736987,0.0003192383,0.003659158,0.004190277,0.00831848,0.004497007,0.001604511,0.0003917633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003504436,"about_ca_system_score_gemma":0.001805936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005007898,"about_ca_topic_score_gemma":0.005678614,"domain_scores_codex":[0.9928676,0.005151987,0.0003308154,0.0004591907,0.0007486955,0.0004416653],"domain_scores_gemma":[0.9700822,0.0262591,0.001436041,0.0003831435,0.001371389,0.0004681203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001168679,0.00005489391,0.01654829,0.0003113913,0.00001708779,0.0006084581,0.9453068,0.0002508725,0.00388642,0.009914687,0.002271962,0.02071228],"study_design_scores_gemma":[0.000008633318,0.00004538442,0.009917419,0.0003185495,0.00001828248,0.0001513114,0.9481923,0.002529382,0.001884529,0.003502464,0.03338624,0.00004561105],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9660575,0.0008798254,0.007310978,0.00896322,0.0001077639,0.0001868917,0.0007249712,0.00004876235,0.01571993],"genre_scores_gemma":[0.9920474,0.000706656,0.003909224,0.0006280135,0.00007489194,0.0001700813,0.000381793,0.00005059802,0.002031327],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00919101,"threshold_uncertainty_score":0.04860729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4010529409893426,"score_gpt":0.4446230285398389,"score_spread":0.04357008755049635,"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."}}