{"id":"W2019065492","doi":"10.1186/1471-2288-10-8","title":"Harnessing Social Networks along with Consumer-Driven Electronic Communication Technologies to Identify and Engage Members of 'Hard-to-Reach' Populations: A Methodological Case Report","year":2010,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Popularity; Population; Referral; Social media; Sample (material); Internet privacy; Sampling (signal processing); Public relations; Set (abstract data type); Psychology; Business; Marketing; Medicine; Family medicine; Computer science; Social psychology; World Wide Web; Political science; Environmental health; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0643605,0.00121051,0.0006606121,0.004431497,0.0128002,0.007438501,0.004356523,0.005385957,0.002178465],"category_scores_gemma":[0.06549037,0.000974139,0.0009152347,0.003203238,0.01109896,0.005633255,0.01193169,0.003074703,0.0009100114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003840876,"about_ca_system_score_gemma":0.006395131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003241622,"about_ca_topic_score_gemma":0.009069777,"domain_scores_codex":[0.8963365,0.08860594,0.003384663,0.002268471,0.006911932,0.002492514],"domain_scores_gemma":[0.9261865,0.05320801,0.007537439,0.006591972,0.004372779,0.002103252],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"case_report","study_design_scores_codex":[0.000213929,0.001360688,0.04584458,0.002573752,0.0001062066,0.05624855,0.716123,0.000599554,0.00298445,0.03360016,0.006638363,0.1337068],"study_design_scores_gemma":[0.0001324025,0.001388721,0.01065725,0.004299956,0.0001906178,0.06977698,0.7645907,0.002287361,0.005355763,0.01792242,0.1232295,0.0001682745],"study_design_candidate":"case_report","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7804084,0.006634055,0.1147129,0.02633024,0.0006949414,0.0144932,0.0003174204,0.0001786675,0.0562302],"genre_scores_gemma":[0.8458205,0.008277384,0.1224322,0.004846103,0.0003806146,0.01009871,0.0001389793,0.000118981,0.007886604],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9356395,"threshold_uncertainty_score":0.3403749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7336373005663528,"score_gpt":0.6383844795544736,"score_spread":0.09525282101187915,"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."}}