{"id":"W2971162800","doi":"10.1007/s10728-019-00383-9","title":"Co-production and Managing Uncertainty in Health Research Regulation: A Delphi Study","year":2019,"lang":"en","type":"article","venue":"Health Care Analysis","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Wellcome Trust; Wellcome","keywords":"Responsible Research and Innovation; Public relations; Biosecurity; Context (archaeology); Public health; Political science; Normative; Delphi method; Corporate governance; Philosophy of medicine; Engineering ethics; Sociology; Business; Law; Medicine; Engineering; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.2427432,0.001249481,0.00134124,0.005021188,0.01514594,0.01526413,0.004075391,0.007036607,0.00281068],"category_scores_gemma":[0.1856513,0.001910961,0.001461575,0.003632813,0.02704565,0.01577874,0.02228391,0.009206499,0.0005860562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01429062,"about_ca_system_score_gemma":0.02249345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00660055,"about_ca_topic_score_gemma":0.004463002,"domain_scores_codex":[0.6550131,0.3044084,0.008013564,0.005252304,0.01224263,0.01506997],"domain_scores_gemma":[0.6607791,0.3003445,0.008235307,0.005231982,0.01761065,0.007798502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007549616,0.0001101264,0.003068977,0.0003574528,0.00002147043,0.0003694967,0.9810312,0.0004637763,0.0004752052,0.006028145,0.000631162,0.00736744],"study_design_scores_gemma":[0.00001557621,0.0001464643,0.001098763,0.0003616248,0.00001081015,0.0001505655,0.9891168,0.001222773,0.0002667525,0.002660718,0.004895925,0.00005321893],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9649129,0.0005423586,0.01345668,0.01054942,0.0001098972,0.001711995,0.0000624116,0.00003725125,0.00861725],"genre_scores_gemma":[0.9894409,0.0005788949,0.005907601,0.001914126,0.0000263129,0.001350149,0.00002823843,0.00002642511,0.00072742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.984854,"threshold_uncertainty_score":0.9338325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2243643183053534,"score_gpt":0.5639428038899815,"score_spread":0.3395784855846282,"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."}}