{"id":"W2989645410","doi":"10.1111/ger.12449","title":"If we cannot measure it, we cannot improve it: Understanding measurement problems in routine oral/dental assessments in Canadian nursing homes—Part I","year":2019,"lang":"en","type":"article","venue":"Gerodontology","topic":"Dental Health and Care Utilization","field":"Dentistry","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates - Health Solutions","keywords":"Medicine; Measure (data warehouse); Dental technology; Nursing; Dentistry; Data mining","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013599,0.0003802656,0.0006328535,0.0006397046,0.0001434833,0.00008697707,0.0003444391,0.00043621,0.0004336536],"category_scores_gemma":[0.0001034883,0.0004239036,0.0000861622,0.0006484263,0.0000818027,0.0003073906,0.00005143763,0.0005691063,0.0002128355],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0122919,"about_ca_system_score_gemma":0.001881187,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3673392,"about_ca_topic_score_gemma":0.9913578,"domain_scores_codex":[0.99554,0.0004288347,0.0008920577,0.0007932227,0.0008004176,0.001545471],"domain_scores_gemma":[0.9986051,0.00004472646,0.0002545461,0.0004454007,0.0001516535,0.0004985129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000245107,0.0003932779,0.957516,0.0006569908,0.00007845343,0.000387679,0.002428694,0.0003072198,0.001064372,0.001788783,0.02090095,0.01423247],"study_design_scores_gemma":[0.02170696,0.001534477,0.841051,0.007424593,0.0002047063,0.0008081397,0.04952859,0.006683154,0.0007032449,0.003041153,0.06414423,0.003169701],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.933765,0.002844524,0.0009614962,0.00711501,0.01452449,0.003747965,0.0002575837,0.0001446211,0.03663931],"genre_scores_gemma":[0.9975592,0.00007022398,0.00003748895,0.0007006083,0.0001089487,0.00007332172,0.0001230049,0.00005348247,0.001273684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6240186,"threshold_uncertainty_score":0.9998213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08125628799904357,"score_gpt":0.342740451302491,"score_spread":0.2614841633034474,"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."}}