{"id":"W4407908152","doi":"10.1002/adma.202414154","title":"An Integrated Virtual Screening Platform to Identify Potent Co‐Assembled Nanodrugs for Cancer Treatment","year":2025,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Key Research and Development Program of Zhejiang Province; Science and Technology Department of Zhejiang Province; National Key Research and Development Program of China; Zhejiang University; National Natural Science Foundation of China","keywords":"Materials science; Nanotechnology; Cancer; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006917798,0.0004008962,0.0006332587,0.0002195587,0.0003054065,0.0003379945,0.0004334944,0.0001148618,0.00043276],"category_scores_gemma":[0.0001526201,0.0003433038,0.00008912267,0.0003100505,0.00004796274,0.0007546282,0.00007984535,0.00004066578,0.0001646483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006315226,"about_ca_system_score_gemma":0.000282004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006413382,"about_ca_topic_score_gemma":0.0002260173,"domain_scores_codex":[0.997332,0.0001079917,0.0007140756,0.0007763797,0.000333007,0.0007365324],"domain_scores_gemma":[0.998433,0.000176241,0.0002029667,0.0006146287,0.0003491323,0.0002240286],"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":[0.00158478,0.0001775378,0.00002608164,0.00003513359,0.00003693303,0.000007672937,0.0002054879,0.00488444,0.9716724,0.0005873478,0.000347334,0.0204349],"study_design_scores_gemma":[0.002381431,0.000538675,0.0002462824,0.0001960216,0.00007924045,0.000001620587,0.0004335135,0.0001128033,0.9877946,0.0002683798,0.007578103,0.0003692809],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973709,0.00008892123,0.02089326,0.0003095438,0.002105587,0.001668284,0.0008388457,0.0003353923,0.00005114757],"genre_scores_gemma":[0.9822263,0.00003376798,0.01483587,0.0006033871,0.0001452631,0.001459597,0.0001115311,0.00005487481,0.0005293708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02006562,"threshold_uncertainty_score":0.9999019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02466127726772809,"score_gpt":0.3507336154570585,"score_spread":0.3260723381893304,"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."}}