{"id":"W1828725948","doi":"10.18438/b8f32k","title":"Call for Studies on Quality Improvement for Inclusion in Systematic Review","year":2010,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inclusion (mineral); Computer science; Quality (philosophy); Data science; Psychology; Epistemology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3475626,0.002849395,0.01655938,0.01989843,0.006372115,0.01224627,0.0082132,0.04959703,0.0359607],"category_scores_gemma":[0.7257193,0.005237858,0.01862338,0.01644882,0.007732852,0.01919533,0.008153114,0.02269163,0.01024421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01544593,"about_ca_system_score_gemma":0.05304027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01004961,"about_ca_topic_score_gemma":0.02228096,"domain_scores_codex":[0.612263,0.1580599,0.1510992,0.009108026,0.06454036,0.004929592],"domain_scores_gemma":[0.1353844,0.5741934,0.06723608,0.03692349,0.1662755,0.0199872],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005057668,0.0002708317,0.003392825,0.2741632,0.004304402,0.001179116,0.001641558,0.0004503918,0.002198902,0.005292415,0.5848117,0.1172369],"study_design_scores_gemma":[0.01321833,0.001695824,0.02093467,0.2995356,0.01073241,0.001534306,0.00370692,0.001979734,0.001919833,0.03576147,0.6073703,0.001610651],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002610586,0.06304876,0.005322264,0.7374593,0.159291,0.01842343,0.004458307,0.0008826816,0.008503595],"genre_scores_gemma":[0.03377141,0.04076151,0.07084904,0.6932111,0.0638487,0.08009492,0.004935976,0.0006394396,0.01188791],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.6524373,"threshold_uncertainty_score":0.8045714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.179372288531449,"score_gpt":0.5163316952823939,"score_spread":0.3369594067509449,"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."}}