{"id":"W2911285538","doi":"10.7189/jogh.09.010701","title":"Exploring individual and demographic characteristics and their relation to CHNRI Criteria from an international public stakeholder group: an analysis using random intercept and logistic regression modelling","year":2019,"lang":"en","type":"article","venue":"Journal of Global Health","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children; SickKids Foundation; Centre for Global Health Research","funders":"","keywords":"Stakeholder; Likert scale; Logistic regression; Weighting; Public health; Psychology; Scale (ratio); Applied psychology; Medicine; Statistics; Geography; Public relations; Political science; Nursing; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.004148097,0.0001534921,0.0006069945,0.0003821554,0.0001232452,0.0002111651,0.0001547741,0.0001549286,0.00002326863],"category_scores_gemma":[0.0009283005,0.0001133896,0.00006718829,0.000348637,0.0001026465,0.0008643356,0.000137163,0.0008392996,3.31423e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002597053,"about_ca_system_score_gemma":0.0002173974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000214414,"about_ca_topic_score_gemma":0.000232464,"domain_scores_codex":[0.9975932,0.0003191527,0.0008414683,0.0003323948,0.0006623883,0.0002514541],"domain_scores_gemma":[0.9974404,0.000733155,0.0004643365,0.0002160639,0.0004397539,0.0007062991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003023801,0.0002029904,0.9646297,0.0001287129,0.0004307314,0.00001943801,0.002352646,0.0002425549,0.0002528076,0.0007244666,0.000002713899,0.02798944],"study_design_scores_gemma":[0.002110544,0.001777272,0.8663993,0.0008026601,0.0001669793,0.00007619113,0.001530362,0.1238795,0.00000221099,0.00312335,0.00002176953,0.0001099079],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.961063,0.0003331943,0.03626429,0.001749232,0.0002929085,0.0001986457,0.00008069356,0.000009606244,0.000008378154],"genre_scores_gemma":[0.9870895,0.002490189,0.009562585,0.0005120843,0.0002777495,0.000001200148,0.00005226663,0.00001269157,0.00000174065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1236369,"threshold_uncertainty_score":0.4623892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6972447414534144,"score_gpt":0.552077227998177,"score_spread":0.1451675134552374,"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."}}