{"id":"W4385215133","doi":"10.2196/46322","title":"Web-Based Application Based on Human-in-the-Loop Deep Learning for Deidentifying Free-Text Data in Electronic Medical Records: Development and Usability Study","year":2023,"lang":"en","type":"article","venue":"Interactive Journal of Medical Research","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Illawarra Shoalhaven Local Health District; Australian Government; South Eastern Sydney Local Health District","keywords":"Usability; Computer science; Human-in-the-loop; Loop (graph theory); World Wide Web; Web application; Human–computer interaction","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":["metaresearch","research_integrity"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06062584,0.0001372021,0.000317168,0.0009800949,0.0003003726,0.0001728842,0.004351377,0.0001420743,0.00006678122],"category_scores_gemma":[0.05021178,0.0001027898,0.00004245327,0.001323953,0.0001249763,0.0003151757,0.0008748883,0.004578176,0.00001126848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005993629,"about_ca_system_score_gemma":0.002341435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004303653,"about_ca_topic_score_gemma":0.005413454,"domain_scores_codex":[0.9886501,0.004030493,0.0009323744,0.0005923087,0.005122063,0.0006726679],"domain_scores_gemma":[0.9794897,0.01861896,0.0002760078,0.000827235,0.0004653951,0.0003226338],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000535309,0.001340435,0.2132432,0.0002316447,0.0000349842,0.0004323331,0.00394172,0.0007735546,0.00004208493,0.0003264652,0.0005932002,0.7785051],"study_design_scores_gemma":[0.002607095,0.001131653,0.1153857,0.0005250084,0.000002629313,0.00001861917,0.00138425,0.8744946,0.00002791008,0.0005649924,0.003760444,0.00009704463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8950799,0.00009787933,0.08075076,0.02298571,0.0001437324,0.000864971,7.045555e-7,0.00002491977,0.00005146121],"genre_scores_gemma":[0.9984785,0.00002802144,0.0009560373,0.0002503865,0.0001219628,0.0001315376,0.000008928185,0.00001329736,0.00001133079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8737211,"threshold_uncertainty_score":0.9977183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1534570053586378,"score_gpt":0.5170091853888534,"score_spread":0.3635521800302157,"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."}}