{"id":"W4281657659","doi":"10.1016/j.jclinepi.2022.05.012","title":"Differentiating between mapping reviews and scoping reviews in the evidence synthesis ecosystem","year":2022,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":91,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University; Public Health Ontario; University of Toronto; St. Michael's Hospital","funders":"","keywords":"Systematic review; Grey literature; Data extraction; Context (archaeology); Scope (computer science); Data science; Inclusion (mineral); Management science; MEDLINE; Medicine; Knowledge management; Computer science; Psychology; Political science; Geography; Engineering","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":["metaresearch","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4063342,0.0001405184,0.003149592,0.0001962174,0.0008262058,0.000005750546,0.0007524869,0.000124738,0.0003482007],"category_scores_gemma":[0.5507695,0.00008335762,0.0002936664,0.0004455283,0.00008821434,0.0001968968,0.0003335603,0.002654349,0.00003780478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001581344,"about_ca_system_score_gemma":0.0005673972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006122004,"about_ca_topic_score_gemma":0.0001108348,"domain_scores_codex":[0.770963,0.2089898,0.0184347,0.0003851988,0.0004016629,0.0008256092],"domain_scores_gemma":[0.2450044,0.7327939,0.02091356,0.0006473452,0.0001763239,0.0004644551],"domain_codex":null,"domain_gemma":"methods","domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001437443,0.00001053472,0.9585096,0.0009738568,0.000007328423,0.00000316046,0.002244241,0.000003866505,0.000003034302,0.0001868581,0.007910175,0.03013302],"study_design_scores_gemma":[0.0004665063,0.0002433844,0.7839786,0.01046775,0.00004456578,0.00002977673,0.002475889,0.0001519265,1.577469e-7,0.001113626,0.2009134,0.0001143184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8302435,0.01231228,0.006104073,0.146322,0.001994346,0.002803622,0.00001543974,0.000009989549,0.0001946816],"genre_scores_gemma":[0.860667,0.03270553,0.007432607,0.09632604,0.002304155,0.000515221,7.563694e-7,0.0000154031,0.0000332502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5259585,"threshold_uncertainty_score":0.9996465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9541313891114885,"score_gpt":0.7807484447028614,"score_spread":0.1733829444086271,"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."}}