{"id":"W2072583156","doi":"10.1353/cpr.2013.0033","title":"Using the Delphi and Snow Card Techniques to Build Consensus Among Diverse Community and Academic Stakeholders","year":2013,"lang":"en","type":"article","venue":"Progress in community health partnerships","topic":"Community Health and Development","field":"Health Professions","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Minority Health and Health Disparities; York University; New York City Health and Hospitals Corporation","keywords":"Community-based participatory research; Participatory action research; Delphi method; Community engagement; Public relations; Stakeholder engagement; Nominal group technique; Sociology; Medical education; Knowledge management; Medicine; Political science; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01371477,0.0004451425,0.0007674625,0.0003959377,0.009889248,0.00006683648,0.0009896405,0.0004780827,0.00003174559],"category_scores_gemma":[0.001396917,0.0003727541,0.00004472233,0.000691712,0.001233911,0.0002333589,0.002379016,0.01180385,0.00001715988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007723235,"about_ca_system_score_gemma":0.001008708,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08613709,"about_ca_topic_score_gemma":0.09155701,"domain_scores_codex":[0.975247,0.02112236,0.001340766,0.0002860982,0.0004209096,0.001582835],"domain_scores_gemma":[0.98897,0.007439474,0.0005494502,0.001582391,0.0003217574,0.001136973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009999717,0.0001451444,0.8490433,0.001383309,0.00002064334,0.000002095587,0.09887034,0.000001958578,0.000004115389,0.0005025216,0.004070564,0.045856],"study_design_scores_gemma":[0.001470521,0.0004314847,0.6299142,0.003355952,0.00002389038,0.00001871905,0.3480576,0.0004556502,0.00001977569,0.002439561,0.01318452,0.0006280947],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636856,0.00190576,0.00006303054,0.02731074,0.0001883126,0.005926109,0.00002687506,0.0002601085,0.0006334226],"genre_scores_gemma":[0.9781736,0.0007591375,0.005730546,0.01405842,0.00006763185,0.001088492,0.00002829487,0.00005371685,0.00004018261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2491873,"threshold_uncertainty_score":0.9998724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5672710809990507,"score_gpt":0.5194501251037069,"score_spread":0.04782095589534374,"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."}}