{"id":"W6977083925","doi":"10.6084/m9.figshare.15079883","title":"Additional file 1 of Combining evidence and values in priority setting: testing the balance sheet method in a low-income country","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Balance sheet; Balance (ability); Key (lock); Sample (material)","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002756034,0.0001011088,0.0001778775,0.00008049413,0.0000879,0.00006389838,0.0007597816,0.00006759643,0.08214647],"category_scores_gemma":[0.03620631,0.00009449955,0.00002086911,0.0007861267,0.00002902974,0.0002744911,0.0008209728,0.0003049446,0.0000280519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007018042,"about_ca_system_score_gemma":0.0003083297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008009792,"about_ca_topic_score_gemma":0.00001873326,"domain_scores_codex":[0.9988185,0.0001722018,0.0002427638,0.0003300682,0.0002390142,0.0001974541],"domain_scores_gemma":[0.9865429,0.0127085,0.0001747792,0.0004098797,0.0001418736,0.00002208855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000124522,0.00003097318,0.0008903861,0.0002202856,0.00000335836,0.0000859323,0.0005612936,0.0003571631,0.00003487607,0.0001223808,0.9894323,0.008259847],"study_design_scores_gemma":[0.0003164298,0.00007590537,0.3105253,0.05606554,0.000002343813,0.0001481586,0.0001786762,0.5619248,0.0003568613,0.005390444,0.06454058,0.0004749534],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.002061095,0.001200903,0.0003889034,0.0007613071,0.00008527291,0.0003061313,0.993476,0.0004773523,0.001243029],"genre_scores_gemma":[0.08660791,0.000003400904,0.8642232,0.000494255,0.00007974113,0.0004995348,0.04795003,0.00002492326,0.0001169775],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.945526,"threshold_uncertainty_score":0.9719121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04637372375393044,"score_gpt":0.2826735906364066,"score_spread":0.2362998668824762,"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."}}