{"id":"W4410480427","doi":"10.1002/ange.202503259","title":"Mitigating Molecular Aggregation in Drug Discovery With Predictive Insights From Explainable AI","year":2025,"lang":"en","type":"article","venue":"Angewandte Chemie","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Bundesministerium für Bildung und Forschung","keywords":"Drug discovery; Drug; Chemistry; Nanotechnology; Materials science; Pharmacology; Medicine; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001437101,0.0006217258,0.0006402267,0.001092645,0.0003443039,0.0008199622,0.0007519274,0.0007243083,0.001171986],"category_scores_gemma":[0.004976642,0.000259246,0.0006266563,0.0004412752,0.0009721802,0.001164738,0.0008563277,0.001035318,0.00009060864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001027321,"about_ca_system_score_gemma":0.0007628705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002869985,"about_ca_topic_score_gemma":0.00310384,"domain_scores_codex":[0.9995276,0.000231732,0.0000162045,0.00008664324,0.00009630896,0.00004162861],"domain_scores_gemma":[0.9969241,0.002201625,0.0004168078,0.0002157531,0.0001644546,0.00007721254],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001037151,0.00006795525,0.004537786,0.0001114864,0.00009761611,0.0001142288,0.00004988692,0.9262704,0.003244259,0.04663359,0.0006869222,0.01808214],"study_design_scores_gemma":[0.000003663551,0.00001745361,0.0002110529,0.00000237921,0.000007091665,0.000008832456,0.00000292779,0.9866789,0.00027951,0.01264246,0.0001425551,0.000003153516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.343528,0.00133298,0.6442741,0.002704073,0.0001087162,0.00009547238,0.0003161384,0.0006893277,0.006951248],"genre_scores_gemma":[0.9758109,0.0003182843,0.02265358,0.000179238,0.0000484413,0.00005716256,0.0001169232,0.00002332532,0.0007921615],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002869985,"threshold_uncertainty_score":0.007600188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00645373569589845,"score_gpt":0.2483747624792257,"score_spread":0.2419210267833272,"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."}}