{"id":"W4229000427","doi":"10.2196/32456","title":"Exploring Human-Data Interaction in Clinical Decision-making Using Scenarios: Co-design Study","year":2022,"lang":"en","type":"article","venue":"JMIR Human Factors","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Connected Health Cities","keywords":"Pulmonary disease; Work (physics); Health professionals; Health care; Decision support system; Space (punctuation); Knowledge management; Clinical decision making; Medicine; Computer science; Engineering; Data mining; Intensive care medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06191809,0.001522384,0.001057846,0.002702056,0.004383375,0.004441781,0.00268194,0.003766051,0.006118021],"category_scores_gemma":[0.1095518,0.00100425,0.001980893,0.001521192,0.00400458,0.004353957,0.005783763,0.002643103,0.0009722076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004475628,"about_ca_system_score_gemma":0.006170845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001286051,"about_ca_topic_score_gemma":0.002646841,"domain_scores_codex":[0.8907267,0.09819286,0.002775963,0.003802533,0.002330483,0.002171444],"domain_scores_gemma":[0.6873953,0.2739753,0.0104336,0.009500341,0.01269999,0.005995356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.006611773,0.02462317,0.1392103,0.009758246,0.001129537,0.00523827,0.5853664,0.02353419,0.007831633,0.02327014,0.006027499,0.1673988],"study_design_scores_gemma":[0.006971487,0.04726705,0.05491297,0.007947615,0.001545637,0.003155265,0.6112431,0.07417149,0.01972719,0.04263069,0.1293967,0.001030711],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9101948,0.0006780329,0.06861372,0.001138579,0.0001219284,0.01038934,0.0004202911,0.0001240503,0.008319141],"genre_scores_gemma":[0.9040895,0.0003607821,0.07790358,0.0006244763,0.00004392142,0.0155311,0.0002717445,0.00004190195,0.001132891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06191809,"threshold_uncertainty_score":0.3274581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5343941342951667,"score_gpt":0.5162282768176758,"score_spread":0.01816585747749089,"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."}}