{"id":"W4379521675","doi":"10.1136/annrheumdis-2023-eular.353","title":"POS0588-HPR DISCOVERING THE POTENTIAL OF DIGITAL BIOMARKERS IN THE WORK PROCESS OF THE RHEUMATOLOGY HEALTHCARE PROFESSIONALS, A DESIGN THINKING APPROACH. PRELIMINARY RESULTS OF THE HEALTHCARE PROFESSIONALS PERSPECTIVE","year":2023,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Koninklijk Nederlands Genootschap voor Fysiotherapie; ZonMw; Arthritis Society; Dutch Arthritis Society; Pfizer","keywords":"Medicine; Health professionals; Health care; Perspective (graphical); Work (physics); Knowledge management; Computer science; Engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009035766,0.0002159892,0.0003878076,0.000100527,0.0002016245,0.00001851182,0.001262967,0.0001090982,0.000002205926],"category_scores_gemma":[0.0009866644,0.00008879349,0.0002577541,0.001366417,0.0003788879,0.0001421586,0.0002721328,0.0003017915,5.628194e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003325797,"about_ca_system_score_gemma":0.0003214186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002000491,"about_ca_topic_score_gemma":0.000006618892,"domain_scores_codex":[0.9973988,0.0004794027,0.0008044305,0.000207034,0.0007796945,0.0003306642],"domain_scores_gemma":[0.9977377,0.0008704168,0.000464952,0.0006892069,0.0001831102,0.00005459497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.004485659,0.006431279,0.04916728,0.08520784,0.0039054,0.000005862207,0.4131141,0.3451607,0.0002993032,0.01439555,0.05007964,0.02774737],"study_design_scores_gemma":[0.001116744,0.0002386626,0.7667592,0.02497474,0.0001792979,0.00002453841,0.1447441,0.03010671,0.001275814,0.03010338,0.00001263287,0.0004641175],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9526802,0.003850355,0.0001812302,0.0404453,0.0007740641,0.001679437,0.0002875204,0.00005704832,0.00004486691],"genre_scores_gemma":[0.9994855,0.0001722301,0.00003312665,0.00007363092,0.00001808008,0.0001494156,0.00001840847,0.0000266442,0.00002297017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7175919,"threshold_uncertainty_score":0.3620894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02754729154034986,"score_gpt":0.3043936982033117,"score_spread":0.2768464066629618,"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."}}