{"id":"W3199934193","doi":"10.2196/32921","title":"Assessing a Smartphone App (AICaries) That Uses Artificial Intelligence to Detect Dental Caries in Children and Provides Interactive Oral Health Education: Protocol for a Design and Usability Testing Study","year":2021,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Dental Health and Care Utilization","field":"Dentistry","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Dental and Craniofacial Research","keywords":"Usability; Early childhood caries; Protocol (science); Medicine; Smartphone app; Medical education; Oral health; Internet privacy; Computer science; Family medicine; Alternative 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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002842692,0.0002146341,0.000352166,0.0002372032,0.0006040836,0.001404721,0.0001965378,0.00008824064,0.00002149996],"category_scores_gemma":[0.002674909,0.000206542,0.00002998295,0.0009417072,0.0002163511,0.0008081123,0.0003896667,0.0004538975,0.000005351197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004383,"about_ca_system_score_gemma":0.002223095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001000688,"about_ca_topic_score_gemma":0.006371317,"domain_scores_codex":[0.9955595,0.001766212,0.0006023064,0.0008224103,0.0006174406,0.0006321103],"domain_scores_gemma":[0.9974628,0.001110059,0.0001569534,0.0003225814,0.000627836,0.0003197525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001673661,0.001611814,0.5284095,0.001163108,0.00001324551,0.00001218763,0.001444323,0.000007415375,0.0002532997,0.0000631571,0.000263926,0.4650843],"study_design_scores_gemma":[0.001547784,0.004932858,0.9399883,0.003462714,0.000004725041,0.0001486177,0.02792462,0.000710736,0.01423059,0.006062601,0.0005469219,0.000439557],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.188445,0.000005254334,0.005131248,0.00007629558,0.00001373975,0.8062558,0.00001361367,0.0000467943,0.00001231589],"genre_scores_gemma":[0.2051228,6.490213e-8,0.008206233,0.0000700158,0.00006553835,0.7864791,0.000009432152,0.000023712,0.00002317477],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.4646448,"threshold_uncertainty_score":0.9996319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4540520892783428,"score_gpt":0.608424481931241,"score_spread":0.1543723926528981,"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."}}