{"id":"W6885957372","doi":"10.1371/journal.pone.0307306.s001","title":"PRISMA checklist.","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Frailty in Older Adults","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grey literature; Transitional care; Health care; Inclusion (mineral); Scope (computer science); Population; Best practice; Systematic review","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.08907354,0.004777822,0.008926756,0.0201817,0.005140567,0.01174542,0.01038039,0.006428882,0.408874],"category_scores_gemma":[0.2304657,0.006669604,0.0148159,0.01934212,0.003803166,0.006078827,0.007498278,0.01029187,0.04561867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01509036,"about_ca_system_score_gemma":0.08079386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02105891,"about_ca_topic_score_gemma":0.03259166,"domain_scores_codex":[0.9250244,0.03535255,0.02575113,0.005642396,0.006423939,0.001805459],"domain_scores_gemma":[0.7907475,0.124717,0.0150145,0.01882168,0.0480284,0.002670902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001883157,0.0002942339,0.0006225007,0.3971684,0.00113585,0.0002101919,0.001684506,0.001349804,0.0002715971,0.01491769,0.5299473,0.05051477],"study_design_scores_gemma":[0.01000253,0.0003324864,0.00346138,0.2041564,0.001857594,0.0002166701,0.002945012,0.001662612,0.000554449,0.0381247,0.7362767,0.0004095029],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.000885891,0.005368893,0.01857558,0.01039177,0.004384931,0.4388226,0.5029005,0.004439082,0.01423073],"genre_scores_gemma":[0.001231395,0.001699985,0.04629903,0.001289207,0.0001406594,0.9269454,0.0181633,0.0003836022,0.003847479],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.408874,"threshold_uncertainty_score":0.8431695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03754472102440051,"score_gpt":0.3048246729273641,"score_spread":0.2672799519029636,"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."}}