{"id":"W4392589154","doi":"10.12927/hcq.2024.27253","title":"Practice Paper: Using Reddit Data to Refine Vaccine Messaging for a Plan-Do-Study-Act Communications Approach","year":2024,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Skepticism; Pandemic; Coronavirus disease 2019 (COVID-19); Plan (archaeology); Public health; Public relations; Internet privacy; Best practice; Computer science; Psychology; World Wide Web; Medicine; Political science; Nursing; History","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.07623504,0.0007593955,0.0004878276,0.008288611,0.004853013,0.006800877,0.002893828,0.00164016,0.01571463],"category_scores_gemma":[0.2129424,0.0005423214,0.0005162364,0.006289586,0.003058901,0.006347421,0.00531983,0.003035957,0.002999529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01660219,"about_ca_system_score_gemma":0.0361436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1674014,"about_ca_topic_score_gemma":0.2523905,"domain_scores_codex":[0.9561847,0.02996018,0.002073825,0.003093761,0.0072828,0.001404651],"domain_scores_gemma":[0.7404552,0.174531,0.01619426,0.02196974,0.04178243,0.005067372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005185865,0.000622498,0.1060861,0.002863207,0.0001201141,0.0005579562,0.1436879,0.002764943,0.004105293,0.04206481,0.08446912,0.6121395],"study_design_scores_gemma":[0.0002749485,0.0007369042,0.09170337,0.005223904,0.000223976,0.0003830161,0.1541229,0.02410447,0.007790173,0.03727272,0.6777784,0.0003853096],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.2971496,0.001450244,0.2889245,0.1044509,0.00206778,0.02101536,0.0281618,0.005196486,0.2515833],"genre_scores_gemma":[0.4841762,0.0006347131,0.4788241,0.006853074,0.000266968,0.004832482,0.005844851,0.0005776231,0.01799001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1674014,"threshold_uncertainty_score":0.4031742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2500385225724008,"score_gpt":0.4825463448701635,"score_spread":0.2325078222977627,"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."}}