{"id":"W4410775469","doi":"10.1136/bmj-2024-083866","title":"Core GRADE 6: presenting the evidence in summary of findings tables","year":2025,"lang":"en","type":"article","venue":"BMJ","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Core (optical fiber); Computer science; Information retrieval; Data science; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.001075701,0.00006163473,0.0001093991,0.00009844586,0.0000786666,0.00003989145,0.0009766849,0.00003513891,0.000006756457],"category_scores_gemma":[0.001258277,0.00004574029,0.00002980734,0.0006598218,0.00003962388,0.0001743842,0.0004651028,0.0002241202,0.000002641795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000248671,"about_ca_system_score_gemma":0.0001249811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001295142,"about_ca_topic_score_gemma":0.0001746206,"domain_scores_codex":[0.9990105,0.0001409589,0.0002646192,0.0002011338,0.0001991461,0.0001836274],"domain_scores_gemma":[0.9983773,0.0009743493,0.00008614489,0.0005005559,0.00004377206,0.00001784687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003235594,0.00001359448,0.9412102,0.000194372,0.000004430759,0.000009347256,0.001174835,0.000808836,0.0002079506,0.03297929,0.01771411,0.00567987],"study_design_scores_gemma":[0.000160027,0.00002878979,0.7860961,0.001693175,0.000004165372,0.000007427434,0.0001323038,0.1944935,0.0008017391,0.008812944,0.007638102,0.0001317567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8384359,0.004539963,0.02331649,0.1202861,0.001266181,0.001385653,0.000002760209,0.0001958035,0.01057116],"genre_scores_gemma":[0.9909923,0.00003059047,0.006709436,0.0004558468,0.00003643059,0.00002689055,5.211292e-7,0.000003156399,0.001744801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1936847,"threshold_uncertainty_score":0.1957875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1102951727315951,"score_gpt":0.3971411732511367,"score_spread":0.2868460005195416,"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."}}