{"id":"W4239204192","doi":"10.21203/rs.2.14912/v3","title":"Database combinations to retrieve systematic reviews in Overviews of reviews: A methodological study","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Database; Information retrieval; Systematic review; Data science; Political science; MEDLINE","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","metaepi_narrow","metaepi_broad","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.7565724,0.0008861696,0.02530496,0.002901456,0.000189776,0.001088571,0.009171115,0.0003638582,0.005179704],"category_scores_gemma":[0.8132768,0.0004208008,0.004622182,0.01286802,0.0001381645,0.0002257582,0.006723096,0.002621983,0.009090279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003357122,"about_ca_system_score_gemma":0.0004173868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001741854,"about_ca_topic_score_gemma":0.000351402,"domain_scores_codex":[0.2507852,0.6551641,0.05718315,0.005937219,0.02962473,0.001305602],"domain_scores_gemma":[0.8127726,0.1162808,0.02403567,0.03418489,0.01109477,0.001631329],"domain_codex":"methods","domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001232051,0.004773481,0.02172354,0.4503853,0.0008897296,0.0002351912,0.02066896,0.0001409384,0.0002156984,0.007985041,0.4829564,0.009902532],"study_design_scores_gemma":[0.003044228,0.004367353,0.03730463,0.3012515,0.003033992,0.00002744028,0.03775488,0.01103368,0.00005900514,0.06930508,0.5292622,0.003556036],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.05056477,0.4279999,0.1021005,0.014502,0.001945707,0.3876911,0.001605211,0.00006843138,0.01352232],"genre_scores_gemma":[0.7581615,0.04225764,0.1276845,0.001643175,0.0007023746,0.05232374,0.0005929109,0.0002626343,0.01637152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7075967,"threshold_uncertainty_score":0.9999484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9793227972626526,"score_gpt":0.7303971584044431,"score_spread":0.2489256388582095,"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."}}