{"id":"W4318997116","doi":"10.3390/curroncol30020143","title":"Harnessing Real-World Evidence to Advance Cancer Research","year":2023,"lang":"en","type":"review","venue":"Current Oncology","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Health and Medical Research Council; Translational Cancer Research Network; National Breast Cancer Foundation","keywords":"Medicine; Real world data; Randomized controlled trial; Real world evidence; Clinical trial; Cornerstone; Data science; Quality (philosophy); Evidence-based practice; Evidence-based medicine; Data quality; Alternative medicine; Medical physics; Computer science; Pathology; Operations management; Internal medicine","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":[0.2298535,0.002655604,0.009884199,0.01596736,0.001113671,0.01610354,0.004979522,0.007917566,0.01052989],"category_scores_gemma":[0.4891361,0.001757981,0.005205487,0.01197105,0.006522307,0.01608671,0.008698773,0.0115761,0.002075026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00772998,"about_ca_system_score_gemma":0.03096915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003428011,"about_ca_topic_score_gemma":0.004977995,"domain_scores_codex":[0.7709983,0.1841856,0.01779835,0.00520813,0.02031541,0.001494132],"domain_scores_gemma":[0.2589647,0.6918594,0.01677787,0.01640994,0.01451547,0.001472596],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003262306,0.0002259151,0.00258113,0.2413312,0.009925338,0.000377489,0.001107832,0.00529745,0.0003581367,0.1645969,0.01979915,0.5540732],"study_design_scores_gemma":[0.0006282972,0.0004201738,0.003064122,0.4422867,0.007179472,0.000363544,0.001238366,0.002422669,0.0005086808,0.3104904,0.2312014,0.0001962973],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001080336,0.9176562,0.0246199,0.04287622,0.003750934,0.0009500118,0.0006344423,0.0001026065,0.008329488],"genre_scores_gemma":[0.03726093,0.8830758,0.05474515,0.01708681,0.004419203,0.001998001,0.0007893912,0.00008985196,0.0005348338],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7701465,"threshold_uncertainty_score":0.9497278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9444572561004146,"score_gpt":0.7244363435946608,"score_spread":0.2200209125057538,"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."}}