{"id":"W4414530819","doi":"10.1021/acs.jcim.5c01521","title":"Integrated Machine Learning and Structure-Based Virtual Screening Identify Osimertinib as a TNIK Inhibitor for Idiopathic Pulmonary Fibrosis","year":2025,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Fundo para o Desenvolvimento das Ciências e da Tecnologia","keywords":"Idiopathic pulmonary fibrosis; Osimertinib; Virtual screening; IC50; Selumetinib; Combination therapy; Western blot","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003057864,0.0001515168,0.0003402457,0.0002479146,0.0001106769,0.00009404628,0.0000521269,0.0001400948,0.00001015279],"category_scores_gemma":[0.0005007675,0.000122288,0.0001457145,0.0001206007,0.00004625563,0.0005342594,0.00003918212,0.0004224352,3.686519e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004742936,"about_ca_system_score_gemma":0.0001653236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001533287,"about_ca_topic_score_gemma":1.50748e-7,"domain_scores_codex":[0.9987515,0.00002325905,0.0007613078,0.00009620069,0.0002127276,0.0001550666],"domain_scores_gemma":[0.9990534,0.0000672119,0.0002605575,0.00005031046,0.0004047235,0.0001638197],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.03613907,0.0001658338,0.001261614,0.002351489,0.0003158233,0.00002311737,0.0007564967,0.006334792,0.8217567,0.001120613,0.0002683561,0.1295061],"study_design_scores_gemma":[0.002052385,0.0008426168,0.00001997955,0.002147286,0.0002433508,0.0001473019,0.0004975387,0.9646912,0.02721827,0.0002978356,0.001703334,0.0001389089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.879717,0.001599492,0.1173644,0.000813099,0.0001361223,0.0002114424,0.00003057654,0.00002527462,0.0001026106],"genre_scores_gemma":[0.995997,0.00009170899,0.00299877,0.0006668478,0.0001266494,0.000004162813,0.0000818044,0.000008854498,0.00002423335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9583564,"threshold_uncertainty_score":0.4986762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01209683317442715,"score_gpt":0.2820118238544961,"score_spread":0.269914990680069,"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."}}