{"id":"W4412163905","doi":"10.1158/1557-3265.aimachine-a012","title":"Abstract A012: AI-assisted Design of Novel NRF2Mut Inhibitors","year":2025,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Synthesis and Biological Evaluation","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Computational biology; Pharmacology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005062402,0.0001111707,0.0003407675,0.00008423047,0.0001037452,0.00003312763,0.00039442,0.0003792593,0.003025499],"category_scores_gemma":[0.005819605,0.00008096756,0.0001728315,0.0004120297,0.0004650093,0.00004354776,0.0001605978,0.0007708631,0.00003137369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001361092,"about_ca_system_score_gemma":0.0006144145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000251624,"about_ca_topic_score_gemma":0.00002747243,"domain_scores_codex":[0.9975727,0.000211663,0.0008168156,0.0004334645,0.0006161664,0.0003492518],"domain_scores_gemma":[0.9945508,0.004266256,0.0001203585,0.0003789195,0.0005733911,0.0001102335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001035446,0.001447838,0.03610616,0.000333968,0.0001485221,0.00000398823,0.00002017608,0.0001197672,0.6163366,0.0003938679,0.02144502,0.3226086],"study_design_scores_gemma":[0.004057577,0.0003237975,0.3935427,0.001656517,0.00007805675,8.229902e-7,0.0002328905,0.003555838,0.563603,0.0026169,0.02988857,0.0004433211],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9708375,0.00120504,0.0007462048,0.004247148,0.0003505957,0.0003366733,0.00004625478,0.00006256351,0.02216805],"genre_scores_gemma":[0.9974465,0.0004123995,0.0002998894,0.0001852967,0.0003212116,0.000100038,0.000007562647,0.00000961981,0.001217502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3574366,"threshold_uncertainty_score":0.9978859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5758945951923626,"score_gpt":0.5891812392391099,"score_spread":0.01328664404674729,"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."}}