{"id":"W2977724833","doi":"10.2196/14531","title":"A Smartphone App for Improving Clinical Photography in Emergency Departments: Comparative Study","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Digital Imaging in Medicine","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Upload; Photography; Digital photography; Digital camera; Camera phone; mHealth; Computer science; Smartphone app; Emergency department; Digital health; Multimedia; Medicine; Medical emergency; Internet privacy; Artificial intelligence; World Wide Web; Nursing; Health care","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":[0.002562734,0.0005408958,0.0008187699,0.001168748,0.00057497,0.0008354122,0.0004220516,0.0007581645,0.003519717],"category_scores_gemma":[0.006554729,0.0002587834,0.001059332,0.0005577249,0.0004517393,0.001253823,0.0007695833,0.0005626166,0.0005610975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005137721,"about_ca_system_score_gemma":0.0007648814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009521096,"about_ca_topic_score_gemma":0.001784136,"domain_scores_codex":[0.9983296,0.0007053644,0.0002415203,0.0001651187,0.0003797296,0.0001787384],"domain_scores_gemma":[0.9959893,0.00212083,0.0003919353,0.0001300852,0.0009952514,0.000372735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.0365201,0.116191,0.152418,0.02095445,0.001772909,0.002563999,0.0257662,0.0004197799,0.009266916,0.0007420019,0.005912526,0.6274722],"study_design_scores_gemma":[0.0109593,0.3709236,0.5418507,0.002949662,0.003694956,0.003447502,0.03627444,0.002142083,0.006102698,0.0003115418,0.02103895,0.0003045195],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947731,0.001930241,0.0003326866,0.00009283734,0.00004789488,0.001297792,0.0001366617,0.00001434939,0.001374425],"genre_scores_gemma":[0.9861805,0.004385608,0.004358394,0.0003086395,0.00008743324,0.002597542,0.0002434048,0.0000122009,0.001826169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003519717,"threshold_uncertainty_score":0.0135532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09719706247580406,"score_gpt":0.4740223692465502,"score_spread":0.3768253067707461,"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."}}