{"id":"W2905206215","doi":"10.12968/npre.2018.16.12.600","title":"Skin tears: Prediction, prevention, assessment and management","year":2018,"lang":"en","type":"article","venue":"Nurse Prescribing","topic":"Pressure Ulcer Prevention and Management","field":"Health Professions","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nurses Association; Western University","funders":"","keywords":"Medicine; Tears; Best practice; Artificial tears; Skin care; Intensive care medicine; Wound care; Dermatology; Surgery; Nursing; Management","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00114312,0.0001853051,0.0001963479,0.0001845505,0.0009318334,0.00004033377,0.0002039944,0.0001129931,0.001586998],"category_scores_gemma":[0.00002462628,0.0001803486,0.00006045299,0.0001773166,0.0001063933,0.0003112878,0.0003042426,0.0003083473,0.0002929345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001368853,"about_ca_system_score_gemma":0.00005360395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005208238,"about_ca_topic_score_gemma":0.00008432187,"domain_scores_codex":[0.9976645,0.0004776293,0.0005373067,0.0004816906,0.0003506785,0.0004881982],"domain_scores_gemma":[0.9989684,0.00005182855,0.0001832259,0.0004838473,0.0001583292,0.0001544113],"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":[0.0001521951,0.000672665,0.08612446,0.00145101,0.0008505709,0.00002699726,0.009762291,0.0000133115,0.0005210633,0.1959561,0.5785203,0.1259491],"study_design_scores_gemma":[0.002178945,0.0001569463,0.3712473,0.0006789415,0.0002203239,0.000003293204,0.004624547,0.001105524,0.00004336816,0.006051852,0.6134251,0.0002638536],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06705267,0.0002819607,0.0894964,0.00277951,0.004588963,0.005812303,0.00003346705,0.0009813565,0.8289734],"genre_scores_gemma":[0.9229137,0.0001858502,0.01172851,0.001317801,0.0008505241,0.0005799715,0.00003116906,0.00005042674,0.062342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8558611,"threshold_uncertainty_score":0.9993257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05460679317651199,"score_gpt":0.4258950189494362,"score_spread":0.3712882257729242,"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."}}