{"id":"W2912788005","doi":"10.3310/hsdr07040","title":"Developing a reporting guideline to improve meta-ethnography in health research: the eMERGe mixed-methods study","year":2019,"lang":"en","type":"article","venue":"Health Services and Delivery Research","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Health Canada; National Institutes of Health; University of Southampton; Health Services and Delivery Research Programme; National Institute for Health and Care Research; United Kingdom Clinical Research Collaboration; World Health Organization","keywords":"Ethnography; Systematic review; CLARITY; Audit; Guideline; MEDLINE; Sociology; Psychology; Medical education; Management science; Medicine; Management; Political science; Engineering","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":["metaresearch","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.8207802,0.0003842499,0.004717205,0.002771721,0.001473575,0.001438514,0.002849317,0.0001056039,0.001377005],"category_scores_gemma":[0.01841973,0.0001725277,0.0008032746,0.0119273,0.00009919916,0.0003507898,0.002038689,0.001296597,0.0008435143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001950637,"about_ca_system_score_gemma":0.001164678,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01770593,"about_ca_topic_score_gemma":0.01615015,"domain_scores_codex":[0.6557726,0.2483209,0.05672087,0.005863357,0.02883946,0.004482854],"domain_scores_gemma":[0.945025,0.02514774,0.01087207,0.008195128,0.009468291,0.001291775],"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":[0.0001979126,0.0006158383,0.1902574,0.005218273,0.00165038,0.00004488243,0.06048726,0.0003735056,0.0001405022,0.002453478,0.0814127,0.6571479],"study_design_scores_gemma":[0.0007377714,0.002027783,0.09385831,0.0005445648,0.00008031484,0.00001906499,0.3447078,0.02434636,0.00001534415,0.008350186,0.5248227,0.000489819],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9191761,0.02424004,0.00201271,0.04385057,0.0004548984,0.009440972,0.00001614838,0.00001246263,0.0007961001],"genre_scores_gemma":[0.9109086,0.001692657,0.07209107,0.01045694,0.0002355131,0.0009735401,0.00001128759,0.00006014906,0.003570243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8023604,"threshold_uncertainty_score":0.9999344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9279395449326173,"score_gpt":0.714362175974313,"score_spread":0.2135773689583044,"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."}}