{"id":"W7110911185","doi":"10.1371/journal.pone.0325064.s003","title":"PRISMA 2020 Checklist.","year":2025,"lang":"","type":"article","venue":"Figshare","topic":"Assistive Technology in Communication and Mobility","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Checklist; Quality of life (healthcare); Socioeconomic status; Psychological intervention; Population; Scale (ratio); Thematic analysis; Population ageing; Inclusion (mineral)","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":[],"consensus_categories":[],"category_scores_codex":[0.06242704,0.003641485,0.007421688,0.01504002,0.002397658,0.007290595,0.007564315,0.00446488,0.3489941],"category_scores_gemma":[0.1766509,0.0041604,0.01217564,0.01255222,0.003008804,0.005938099,0.00623384,0.005449151,0.02394853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008024108,"about_ca_system_score_gemma":0.03009639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01081105,"about_ca_topic_score_gemma":0.01343644,"domain_scores_codex":[0.9448461,0.0243282,0.02131807,0.003491923,0.004812606,0.001203118],"domain_scores_gemma":[0.8473175,0.1022144,0.01389412,0.008560451,0.02672193,0.001291643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009194717,0.00008648348,0.0004846634,0.6199174,0.001367785,0.0001506791,0.0007886973,0.0006711424,0.0003309369,0.006681537,0.342944,0.02565722],"study_design_scores_gemma":[0.006955367,0.0002847285,0.005569661,0.3305656,0.002401989,0.0003757231,0.001815696,0.002362673,0.0009033754,0.02107976,0.6272416,0.0004437832],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001089443,0.005335445,0.01213669,0.009924541,0.003815642,0.2880216,0.661988,0.006975203,0.01071346],"genre_scores_gemma":[0.003683046,0.002080219,0.04579323,0.001974502,0.0001805208,0.9125285,0.02884354,0.0008358524,0.004080614],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3489941,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09901567889699998,"score_gpt":0.4342762761309628,"score_spread":0.3352605972339628,"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."}}