{"id":"W4322741260","doi":"10.1186/s12874-023-01875-y","title":"Exploring data reduction strategies in the analysis of continuous pressure imaging technology","year":2023,"lang":"en","type":"article","venue":"BMC Medical Research Methodology","topic":"Pressure Ulcer Prevention and Management","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Alberta Health Services; Alberta Health; Foothills Medical Centre; Libin Cardiovascular Institute of Alberta; University of Calgary","funders":"Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Computer science; Reduction (mathematics); Medicine; Data science; Medical physics; Data mining; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04614521,0.001848835,0.001302762,0.004122654,0.001079153,0.004244226,0.002585423,0.001372979,0.002129028],"category_scores_gemma":[0.127139,0.0008708855,0.002574241,0.003804335,0.001879381,0.002161189,0.002612861,0.002336224,0.0007683724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00156576,"about_ca_system_score_gemma":0.004484839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003578449,"about_ca_topic_score_gemma":0.004453415,"domain_scores_codex":[0.9610984,0.02788777,0.00218219,0.001690597,0.006658743,0.000482383],"domain_scores_gemma":[0.8506607,0.1179408,0.00665595,0.01073098,0.0132426,0.0007689612],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002189371,0.001866403,0.03863205,0.004087246,0.001708688,0.0008620301,0.005675231,0.07152439,0.03735362,0.03868184,0.006549557,0.7908696],"study_design_scores_gemma":[0.001218906,0.007500161,0.05596648,0.001772188,0.001338901,0.00143639,0.006087797,0.6866437,0.06873862,0.1124352,0.0563031,0.0005585339],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04566813,0.001099979,0.9465116,0.00197174,0.0001292043,0.001813231,0.0004549984,0.0007030204,0.00164818],"genre_scores_gemma":[0.1126622,0.0003633623,0.883716,0.0003263641,0.00006719712,0.00194176,0.0004499269,0.00009698465,0.0003761303],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9538548,"threshold_uncertainty_score":0.2440422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8783758602578795,"score_gpt":0.6749957086587656,"score_spread":0.2033801515991139,"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."}}