{"id":"W2886606374","doi":"10.1002/jmri.26198","title":"Best practices for MRI systematic reviews and meta‐analyses","year":2018,"lang":"en","type":"review","venue":"Journal of Magnetic Resonance Imaging","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Public Health; Ottawa Hospital; University of Ottawa","funders":"","keywords":"Systematic review; Meta-analysis; Medical physics; Computer science; Medicine; MEDLINE; Management science; Data science; Pathology","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"],"consensus_categories":[],"category_scores_codex":[0.005532107,0.0005409145,0.006621778,0.0004477691,0.0001222208,0.0001958537,0.0003670626,0.0001193078,0.00007557293],"category_scores_gemma":[0.0135511,0.0002997706,0.001628821,0.0002816479,0.0002295466,0.000239012,0.00007662843,0.0009483755,0.00001665224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008261087,"about_ca_system_score_gemma":0.0003513277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001800992,"about_ca_topic_score_gemma":8.541859e-7,"domain_scores_codex":[0.995322,0.0006921526,0.002645741,0.0004001058,0.0005654173,0.000374507],"domain_scores_gemma":[0.9899359,0.002174117,0.006671528,0.0004616216,0.0004604775,0.000296372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001716657,0.00005284523,0.000006278565,0.3198989,0.0008898338,0.0001301745,0.00004643668,1.15638e-7,0.000001875093,0.000008712714,0.006536093,0.6724116],"study_design_scores_gemma":[0.0004142839,0.0002805273,0.000001249828,0.1205354,0.0993214,0.005500783,0.00003181083,0.0004014271,3.175305e-7,0.00002713798,0.7732897,0.0001959451],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[9.297462e-7,0.994446,0.001379646,0.001198184,0.0003722026,0.002168507,0.000005797381,0.0000101569,0.0004186044],"genre_scores_gemma":[7.854537e-7,0.9625114,0.03332301,0.0003896185,0.001064027,0.0001369506,0.000003805444,0.00007901232,0.002491349],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7667536,"threshold_uncertainty_score":0.9999455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2022889902004515,"score_gpt":0.4815954989364937,"score_spread":0.2793065087360422,"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."}}