{"id":"W4386430989","doi":"10.1590/0034-7167-2022-0453","title":"Content validity evidence of the Brazilian version of the Cognitive Symptom Checklist-Work-21","year":2023,"lang":"en","type":"article","venue":"Revista Brasileira de Enfermagem","topic":"Cancer-related cognitive impairment studies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Universidade de São Paulo; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Universidade do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Equivalence (formal languages); Content validity; Checklist; Psychology; Cognition; Context (archaeology); Semantic equivalence; Clinical psychology; Applied psychology; Psychometrics; Cognitive psychology; Linguistics; Computer science; Artificial intelligence; Psychiatry","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":[0.000749253,0.0002494355,0.0005411289,0.0000948595,0.0002043728,0.00002127837,0.0003434101,0.0001109398,0.0001549159],"category_scores_gemma":[0.003238166,0.0001555726,0.0004651507,0.001319037,0.000597172,0.0001133064,0.0004706519,0.0004174892,0.00006977392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002554684,"about_ca_system_score_gemma":0.0002807592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007457598,"about_ca_topic_score_gemma":0.000008834557,"domain_scores_codex":[0.9977026,0.0003779526,0.0005252313,0.0003403543,0.0006853165,0.0003685429],"domain_scores_gemma":[0.9973791,0.0009711673,0.0004124396,0.0005873133,0.0005510338,0.0000989173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005017181,0.0001246131,0.9776881,0.0008844882,0.0002667284,0.00001533085,0.0008461886,0.000005798996,0.008865649,0.0001014989,0.009362374,0.001337552],"study_design_scores_gemma":[0.001240601,0.0001931031,0.9693587,0.008412109,0.0006537681,0.00001662766,0.0007856581,0.00004053756,0.01853168,0.000008205668,0.0006154189,0.0001435211],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947091,0.0008159618,0.00004754848,0.0009855931,0.0003423256,0.001356958,0.00009486821,0.00007939029,0.001568305],"genre_scores_gemma":[0.9962606,0.0003780822,0.00001041428,0.0004884992,0.0001124546,0.00004406748,0.00001124755,0.00003169168,0.002662933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009666035,"threshold_uncertainty_score":0.6344065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1278805235788282,"score_gpt":0.3474685998508227,"score_spread":0.2195880762719944,"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."}}