{"id":"W2754431019","doi":"10.3390/ijerph14091056","title":"Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention","year":2017,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Children's Hospital; Simon Fraser University","funders":"Canadian Institutes of Health Research","keywords":"Analytics; Visual analytics; Delphi method; Stakeholder; Computer science; Data analysis; Social media analytics; Data science; Stakeholder engagement; Knowledge management; Visualization; Data mining; Artificial intelligence; Social media; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.01444929,0.0001028573,0.0002585668,0.0008036739,0.001360392,0.0009447653,0.001275013,0.0000777113,0.0001173842],"category_scores_gemma":[0.002165745,0.00009719315,0.0000653246,0.0002550954,0.0008664625,0.0008047724,0.0004383203,0.0006376916,0.0000161858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001953215,"about_ca_system_score_gemma":0.003147281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001090199,"about_ca_topic_score_gemma":0.00042359,"domain_scores_codex":[0.9941806,0.001053201,0.000587242,0.0002487542,0.003212644,0.0007175161],"domain_scores_gemma":[0.9971775,0.0002205505,0.0005563936,0.0002230718,0.0005105239,0.001311897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006601855,0.004927918,0.04131859,0.00005235373,0.0004574665,0.00005492718,0.01464616,0.00001331998,0.0002002963,0.03194217,0.04335139,0.8623753],"study_design_scores_gemma":[0.002138855,0.01065251,0.171994,0.0003890416,0.000007324818,0.00007045014,0.07822651,0.0008146974,0.0001115528,0.01941781,0.7156538,0.0005234564],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5280867,0.001385316,0.01742093,0.4198008,0.0008558877,0.002473465,0.0003356231,0.00003819786,0.02960306],"genre_scores_gemma":[0.9901462,0.004961163,0.002896996,0.0004954561,0.0004972327,0.00001410358,0.000009718795,0.00001280003,0.000966359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8618518,"threshold_uncertainty_score":0.9999397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2132813063543361,"score_gpt":0.5625165874907857,"score_spread":0.3492352811364496,"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."}}