{"id":"W4412163772","doi":"10.1158/1557-3265.aimachine-a018","title":"Abstract A018: Accelerating drug discovery at an HBCU with AI/ML: Text mining, computational modeling, and drug repurposing approaches","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Drug repositioning; Drug; Repurposing; Drug discovery; Computer science; Medicine; Pharmacology; Bioinformatics; Engineering; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001670747,0.0009107539,0.0005588244,0.002286261,0.0005884097,0.001965288,0.0009286773,0.0005751807,0.007123681],"category_scores_gemma":[0.003507298,0.0003447513,0.0008501285,0.001523922,0.000440706,0.001455153,0.0008217014,0.001264584,0.001972712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009678791,"about_ca_system_score_gemma":0.002371295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00599818,"about_ca_topic_score_gemma":0.007661723,"domain_scores_codex":[0.9993823,0.0001953952,0.00004164848,0.0001079414,0.0002413824,0.00003135825],"domain_scores_gemma":[0.9973541,0.001408765,0.0002213514,0.0002422506,0.0006183356,0.0001550896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004617442,0.0006100883,0.008709525,0.0009841134,0.000245291,0.0004136827,0.0001880881,0.1464927,0.04188643,0.02894266,0.08768767,0.683378],"study_design_scores_gemma":[0.0000957241,0.0002175387,0.001744015,0.00009476845,0.00007233577,0.0001127231,0.00009240476,0.9210845,0.01777709,0.02272672,0.03593386,0.0000483938],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.100737,0.003873433,0.8107602,0.02026491,0.0006980589,0.0008186115,0.006900987,0.03162089,0.02432594],"genre_scores_gemma":[0.2321244,0.002854322,0.748358,0.001525227,0.0003929464,0.0003521652,0.005427094,0.0007772763,0.008188609],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007123681,"threshold_uncertainty_score":0.02383107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2264133334696734,"score_gpt":0.4743242718112853,"score_spread":0.2479109383416118,"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."}}