{"id":"W4417082287","doi":"10.2196/76674","title":"Leveraging AI Large Language Models for Writing Clinical Trial Proposals in Dermatology: Instrument Validation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Expert system; Clinical trial; Subject-matter expert; Model validation","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2671514,0.0009726514,0.001095348,0.002218507,0.0008494313,0.003248442,0.001948816,0.00150695,0.003309796],"category_scores_gemma":[0.5165623,0.0009862789,0.00212503,0.001721087,0.001652418,0.00288759,0.003856169,0.00218206,0.001085465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002690212,"about_ca_system_score_gemma":0.006704638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001275931,"about_ca_topic_score_gemma":0.002476438,"domain_scores_codex":[0.7820355,0.1908765,0.01360083,0.005155798,0.007315807,0.001015676],"domain_scores_gemma":[0.1964958,0.7275827,0.0238715,0.02935867,0.02044036,0.002251043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.03268502,0.01210802,0.1427207,0.01086056,0.003226771,0.0005873597,0.02302787,0.02931434,0.006763774,0.003822383,0.01746027,0.7174229],"study_design_scores_gemma":[0.04593057,0.05918017,0.2834983,0.007237089,0.00822775,0.00251445,0.007710824,0.4479667,0.03288046,0.02171917,0.0815601,0.00157458],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8599808,0.00228035,0.1004321,0.0023531,0.0004297337,0.02325369,0.002033468,0.003014231,0.006222412],"genre_scores_gemma":[0.8155941,0.0006741851,0.1588702,0.001546758,0.0002129706,0.02035908,0.001462741,0.0002332335,0.001046734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2671514,"threshold_uncertainty_score":0.9037328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2268048425356374,"score_gpt":0.5355604158180052,"score_spread":0.3087555732823678,"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."}}