{"id":"W6920569072","doi":"10.6084/m9.figshare.22775956.v1","title":"Additional file 1 of Does type of funding affect reporting in network meta-analysis? A scoping review of network meta-analyses","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto","funders":"","keywords":"Affect (linguistics); Government (linguistics); The Internet; Information system; Access to information","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01476168,0.001564379,0.002280795,0.00662367,0.001098457,0.00243513,0.002589802,0.002488284,0.907191],"category_scores_gemma":[0.2382049,0.001377773,0.002518491,0.009228773,0.0005698199,0.003786475,0.00224474,0.001350344,0.1200056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003259196,"about_ca_system_score_gemma":0.006182027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006177877,"about_ca_topic_score_gemma":0.009838292,"domain_scores_codex":[0.9916408,0.002924968,0.002763962,0.001030734,0.00121649,0.0004229896],"domain_scores_gemma":[0.6501665,0.3062919,0.01789547,0.007507867,0.01655465,0.001583571],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"systematic_review","study_design_scores_codex":[0.001091793,0.0000906785,0.001779612,0.03424424,0.0003384279,0.0000720332,0.0001330501,0.0005891592,0.00007942219,0.002308881,0.9431871,0.01608559],"study_design_scores_gemma":[0.0277022,0.0005591244,0.02421271,0.05541901,0.002056673,0.0007060712,0.0006238703,0.00436208,0.001059515,0.03083878,0.8521131,0.0003468605],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"review","genre_scores_codex":[0.0002754506,0.0001388776,0.001117087,0.0005451801,0.0001150935,0.001296587,0.993727,0.0004363171,0.002348451],"genre_scores_gemma":[0.02193136,0.0013268,0.02977751,0.004930667,0.0009234695,0.07713512,0.8261529,0.002821395,0.03500082],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9852383,"threshold_uncertainty_score":0.1323807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9514273745727079,"score_gpt":0.6169330374805625,"score_spread":0.3344943370921454,"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."}}