{"id":"W4408159463","doi":"10.1016/j.compbiomed.2025.109958","title":"StackTHP: A stacking ensemble model for accurate prediction of tumor-homing peptides in cancer therapy","year":2025,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; King Saud University","keywords":"Homing (biology); Stacking; Cancer therapy; Computer science; Artificial intelligence; Cancer; Computational biology; Cancer research; Medicine; Internal medicine; Chemistry; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003370656,0.00009483975,0.0002016342,0.0001261923,0.00002896095,0.000002207132,0.00009113135,0.00009640738,9.928567e-7],"category_scores_gemma":[0.00009929415,0.0000771275,0.00001856659,0.00008451616,0.0001281277,0.000003756769,0.00005478381,0.0000941544,2.656651e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001422112,"about_ca_system_score_gemma":0.00005456857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004644712,"about_ca_topic_score_gemma":0.00007865571,"domain_scores_codex":[0.9993401,0.0000384629,0.0002876876,0.0001647288,0.0000252228,0.0001438205],"domain_scores_gemma":[0.9996689,0.00006747271,0.00009452111,0.0001112514,0.00003973851,0.00001810166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001288402,0.0001288569,0.4629085,0.0006204802,0.0001628703,0.000001890984,0.003264097,0.02778601,0.3727085,0.005179126,0.003286199,0.122665],"study_design_scores_gemma":[0.005458441,0.0008694048,0.02839554,0.0006898887,0.00001619736,0.000004658313,0.0002878853,0.9459231,0.01056652,0.003468296,0.004148464,0.0001715581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8059295,0.002126662,0.1908453,0.0003556802,0.0002332414,0.0002667536,0.00001246403,0.000006309021,0.0002241174],"genre_scores_gemma":[0.9921669,0.00140913,0.005548649,0.0006580888,0.0000621824,0.00003406478,0.00006032605,0.000005062415,0.00005563087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9181371,"threshold_uncertainty_score":0.3145168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02550576664145451,"score_gpt":0.3544401044366616,"score_spread":0.3289343377952071,"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."}}