{"id":"W4310147208","doi":"10.2196/preprints.44586","title":"Analysis of Fluoride-Free Content on Twitter: Topic Modeling Study (Preprint)","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute for Aging; University Health Network; Public Health Ontario; University of Toronto; University of Waterloo","funders":"","keywords":"Misinformation; Latent Dirichlet allocation; Social media; Computer science; Topic model; Microblogging; Information retrieval; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001891982,0.0003611026,0.0003711014,0.002204393,0.0006646678,0.00139023,0.0003387347,0.0005651594,0.002861047],"category_scores_gemma":[0.005117331,0.0001874091,0.001174046,0.002016854,0.0002604133,0.001565519,0.0005915124,0.0006160843,0.00118663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006135789,"about_ca_system_score_gemma":0.0005139337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008864285,"about_ca_topic_score_gemma":0.007371277,"domain_scores_codex":[0.999384,0.0002519058,0.00005212717,0.0001355859,0.00009903836,0.00007721609],"domain_scores_gemma":[0.9950278,0.003671379,0.0005303568,0.0001957466,0.0004223587,0.0001523678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005377698,0.001048035,0.855184,0.0007876118,0.0003785768,0.0006586525,0.02681763,0.004222245,0.004401236,0.002828165,0.0160676,0.08706854],"study_design_scores_gemma":[0.00003533828,0.0003964847,0.8364703,0.0002392509,0.0002815714,0.0005372245,0.0404822,0.1020496,0.003017094,0.001677314,0.01469786,0.0001157008],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891726,0.0002574441,0.00386724,0.001034232,0.00004906893,0.0001347862,0.003462879,0.00007977902,0.001941848],"genre_scores_gemma":[0.9877321,0.000431126,0.004539473,0.0001213368,0.0001503912,0.0002881208,0.004371596,0.00004539579,0.002320532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008864285,"threshold_uncertainty_score":0.01762539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1745651169131875,"score_gpt":0.3788307077338194,"score_spread":0.2042655908206319,"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."}}