{"id":"W2365773746","doi":"10.2196/publichealth.4831","title":"Medical Institutions and Twitter: A Novel Tool for Public Communication in Japan","year":2016,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Health, Labour and Welfare","keywords":"Social media; The Internet; Microblogging; Medicine; Public health; Medical education; Family medicine; Nursing; World Wide Web; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001790518,0.0005974225,0.0003538767,0.006395207,0.002021044,0.003105009,0.0005677057,0.000845556,0.005254861],"category_scores_gemma":[0.006721576,0.0002856715,0.0005302358,0.005830824,0.0005619127,0.005817298,0.002641181,0.0005702494,0.002622833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009791921,"about_ca_system_score_gemma":0.001326689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004461371,"about_ca_topic_score_gemma":0.006538677,"domain_scores_codex":[0.9980702,0.0006813823,0.000327569,0.0003059093,0.000393574,0.0002214184],"domain_scores_gemma":[0.9947088,0.001713082,0.001658441,0.0004566257,0.0009436128,0.0005194074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006831951,0.0001929043,0.3937433,0.002709709,0.0001956749,0.003056838,0.02993242,0.000539398,0.01041026,0.006639253,0.09785719,0.4540399],"study_design_scores_gemma":[0.00005735914,0.0002632147,0.4862909,0.000945986,0.0005996943,0.002702012,0.04079383,0.01543542,0.007030732,0.005247472,0.4402563,0.0003770772],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7611219,0.01223557,0.0417859,0.01560812,0.003919597,0.00157685,0.04059073,0.003683705,0.1194778],"genre_scores_gemma":[0.9235206,0.004719875,0.0331584,0.001505231,0.002416894,0.0009985955,0.01228164,0.0003421648,0.02105667],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006395207,"threshold_uncertainty_score":0.01757926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1962763999349177,"score_gpt":0.4374454661698885,"score_spread":0.2411690662349708,"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."}}