{"id":"W1963960070","doi":"10.2196/jmir.2409","title":"Social Media and the Empowering of Opponents of Medical Technologies: The Case of Anti-Vaccinationism","year":2013,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ottawa Hospital; University of Ottawa","funders":"","keywords":"Opposition (politics); Social media; Internet privacy; Public relations; Mechanism (biology); Sociology; Political science; Social psychology; Psychology; Computer science; Epistemology; Politics; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01544735,0.00006495085,0.0003561861,0.0001941111,0.0001631525,0.00004895273,0.001450454,0.0002840813,0.001484484],"category_scores_gemma":[0.01958845,0.00003243184,0.0001162552,0.0003451665,0.001105316,0.0001554398,0.0004723824,0.001079727,0.000002651119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000384037,"about_ca_system_score_gemma":0.000533082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0033584,"about_ca_topic_score_gemma":0.0009439956,"domain_scores_codex":[0.9946014,0.0008065403,0.000727625,0.00008961729,0.003522023,0.000252789],"domain_scores_gemma":[0.9952011,0.00326384,0.0003735483,0.0001341063,0.000880654,0.0001468148],"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":[0.0005124996,0.0009807692,0.02155584,0.0004676523,0.0007789647,0.002176424,0.212718,0.000001132621,0.0006152758,0.2710763,0.153575,0.3355422],"study_design_scores_gemma":[0.02135137,0.001709232,0.07432237,0.004463636,0.0002532884,0.003115228,0.6837924,0.005795334,0.01023845,0.1714897,0.02285145,0.0006175689],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8971692,0.001250213,0.0001115228,0.1005186,0.0001481872,0.0001474052,9.596238e-7,0.000004114103,0.000649827],"genre_scores_gemma":[0.9966529,0.002955274,0.00001839102,0.00003692597,0.0002588761,0.000003954279,1.445989e-7,0.000004877792,0.00006863448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4710744,"threshold_uncertainty_score":0.9994283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08048179167678593,"score_gpt":0.4494143574013358,"score_spread":0.3689325657245499,"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."}}