{"id":"W4412784829","doi":"10.1021/acs.jcim.4c02041","title":"Transfer Learning for Heterocycle Retrosynthesis","year":2025,"lang":"en","type":"article","venue":"Journal of Chemical Information and Modeling","topic":"Chemical Synthesis and Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre","funders":"Engineering and Physical Sciences Research Council; King Abdulaziz University; Alzheimer’s Research UK","keywords":"Retrosynthetic analysis; Computer science; Ring (chemistry); Drug discovery; Training set; Artificial intelligence; Machine learning; Synthetic data; Chemistry; Stereochemistry","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":[0.0001654283,0.00005804839,0.0001255928,0.00004741303,0.00003371382,0.00003009995,0.00005838063,0.000078823,0.00000344852],"category_scores_gemma":[0.0001940493,0.0000477511,0.0001336676,0.00003650593,0.00001320176,0.00002513192,0.0000156222,0.00007257967,2.04647e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008515484,"about_ca_system_score_gemma":0.00001821462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.563544e-7,"about_ca_topic_score_gemma":8.462628e-8,"domain_scores_codex":[0.9994726,0.000006741582,0.0003322211,0.00004683865,0.00006365046,0.00007800504],"domain_scores_gemma":[0.9997141,0.00001860907,0.0000552619,0.00004069976,0.0001298772,0.00004146688],"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":[0.0001182597,0.00001054753,0.00005187688,0.00003722492,0.00005538998,3.302265e-8,0.00002594672,0.004086586,0.9739016,0.00007574157,0.0001429377,0.0214938],"study_design_scores_gemma":[0.0004139915,0.0000289816,0.000001971741,0.00004272111,0.00005057082,0.000004007191,0.00007919186,0.09015775,0.8928601,0.0001972794,0.01609623,0.0000671837],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7939481,0.00021545,0.2052859,0.0003348268,0.00001820338,0.00002529313,0.000001120261,0.000002147716,0.0001690257],"genre_scores_gemma":[0.9982168,0.0002273756,0.001128884,0.0003337565,0.00005619404,0.000002033798,0.000009289959,0.00000260005,0.000023062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2042688,"threshold_uncertainty_score":0.1947233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01016185494338797,"score_gpt":0.2511769490775954,"score_spread":0.2410150941342074,"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."}}