{"id":"W3153822422","doi":"10.2196/28805","title":"Analysis of Cyberincivility in Posts by Health Professions Students: Descriptive Twitter Data Mining Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Descriptive statistics; Coursework; Social media; Pharmacy; Medical education; Psychology; Descriptive research; Medicine; Nursing; Computer science; Sociology; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00405389,0.00009307233,0.0003682641,0.0002365594,0.0002445417,0.00002916037,0.0006319041,0.000142699,0.0007073153],"category_scores_gemma":[0.01501152,0.00009738425,0.00003669339,0.002891693,0.0001710997,0.0002329819,0.0001764838,0.0002835265,0.000004658792],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000794191,"about_ca_system_score_gemma":0.01314691,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02963491,"about_ca_topic_score_gemma":0.0616076,"domain_scores_codex":[0.9950204,0.002001872,0.0006708006,0.0004616658,0.001517269,0.0003279187],"domain_scores_gemma":[0.9973611,0.001001918,0.0003038716,0.0005650637,0.0003227212,0.0004453532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005634176,0.003663422,0.6831335,0.00002099916,0.00005168176,5.223135e-7,0.2884724,6.513223e-8,0.000001816808,0.00002123345,0.005109467,0.01951923],"study_design_scores_gemma":[0.0001576357,0.00002857369,0.6788558,0.00009091968,0.00004822846,6.965225e-8,0.3179508,0.00001968572,9.350741e-7,0.00001703405,0.00277471,0.00005555563],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9696503,0.0003521079,0.00001677261,0.02549878,0.002648647,0.001591252,0.00001499023,0.00002075557,0.0002064015],"genre_scores_gemma":[0.9967258,0.0001018174,0.000202371,0.001253717,0.0002780632,0.0008933849,0.0004238568,0.000007822209,0.0001131919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0319727,"threshold_uncertainty_score":0.9932855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1594414097469982,"score_gpt":0.5456550077944058,"score_spread":0.3862135980474075,"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."}}