{"id":"W3006575237","doi":"10.14745/ccdr.v46i23a05","title":"Optimizing communication material to address vaccine hesitancy","year":2020,"lang":"en","type":"article","venue":"Canada Communicable Disease Report","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canadian Immunization Research Network; Public Health Agency; Public Health Agency of Canada","keywords":"Health communication; Risk communication; Best practice; Public relations; Vaccination; Medicine; Public health; Information Dissemination; Product (mathematics); Business; Nursing; Environmental health; Political science; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003983466,0.0001698576,0.000313039,0.00003383275,0.001063035,0.0001510388,0.001097442,0.00005237958,0.0009634267],"category_scores_gemma":[0.0007943701,0.0001920199,0.00007521976,0.0003826139,0.00001380946,0.0002752909,0.0003961354,0.0001913116,0.00001606062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003707869,"about_ca_system_score_gemma":0.002742937,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4418329,"about_ca_topic_score_gemma":0.7106738,"domain_scores_codex":[0.9979675,0.0003223454,0.0004717828,0.0002869301,0.0005191771,0.0004322509],"domain_scores_gemma":[0.9969676,0.0001138702,0.0001772753,0.001339903,0.0002371983,0.001164155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009608218,0.0002840524,0.07985658,0.000239813,0.0002465169,0.006236458,0.01304042,0.002140548,0.0007359154,0.01110937,0.8817982,0.003351292],"study_design_scores_gemma":[0.0004654017,0.00002856716,0.02468615,0.0001350871,0.00009358252,0.000008636632,0.003013479,0.0001199695,0.0001533452,0.0002108887,0.9705447,0.0005402063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6993449,0.006715082,0.0002916433,0.19585,0.0008032804,0.001866113,0.0002012158,0.0005375706,0.09439018],"genre_scores_gemma":[0.9924546,0.0003285354,0.0009223537,0.005086069,0.0002325139,0.00005556147,0.0001514779,0.00002972553,0.0007391913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2931096,"threshold_uncertainty_score":0.9999498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02745516005849771,"score_gpt":0.283504679067122,"score_spread":0.2560495190086243,"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."}}