{"id":"W4413376900","doi":"10.1021/acsomega.5c05484","title":"Integrating ESM-2 and Graph Neural Networks with AlphaFold-2 Structures for Enhanced Protein Function Prediction","year":2025,"lang":"en","type":"article","venue":"ACS Omega","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Science and Technology Council","keywords":"Artificial neural network; Computer science; Graph; Protein function prediction; Protein function; Artificial intelligence; Theoretical computer science; Chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.00009689095,0.0001234849,0.00009311322,0.00004581725,0.0001304143,0.00004326282,0.00007204817,0.0001198808,7.722259e-7],"category_scores_gemma":[0.00008888703,0.00009650696,0.00002705066,0.00009691307,0.000048632,0.000008617312,0.00004409561,0.0001245186,9.484521e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006463527,"about_ca_system_score_gemma":0.00001839418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007793901,"about_ca_topic_score_gemma":0.00002941905,"domain_scores_codex":[0.9994389,0.00002236881,0.0001516118,0.0001797316,0.00005726435,0.0001501413],"domain_scores_gemma":[0.9996489,0.00001448318,0.00008213477,0.0001592644,0.00006879606,0.00002638002],"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":[0.002304027,0.00006153341,0.01566806,0.0005102867,0.0005148511,7.604918e-7,0.0003034338,0.0309913,0.8106167,0.007671695,0.004001329,0.127356],"study_design_scores_gemma":[0.008821502,0.008051311,0.04595599,0.0004231174,0.0004464728,0.00004735446,0.001077972,0.304448,0.5948259,0.007415673,0.02704005,0.001446603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.673275,0.0001691579,0.3255105,0.00006874309,0.0001148408,0.0003707353,0.000005443969,0.00002502112,0.0004606061],"genre_scores_gemma":[0.9941139,0.00001026502,0.004864939,0.0002313514,0.000115891,0.00009313007,0.0001655224,0.00001142165,0.000393561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3208389,"threshold_uncertainty_score":0.393544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00324868575534767,"score_gpt":0.2253501991170538,"score_spread":0.2221015133617061,"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."}}