{"id":"W4316036353","doi":"10.1038/s42004-022-00790-5","title":"Transferring chemical and energetic knowledge between molecular systems with machine learning","year":2023,"lang":"en","type":"article","venue":"Communications Chemistry","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Supercomputing Centre Singapore; Centro Svizzero di Calcolo Scientifico; Ministero dell’Istruzione, dell’Università e della Ricerca; Canada Research Chairs","keywords":"Molecular machine; Computer science; Artificial intelligence; Nanotechnology; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00111987,0.0008802532,0.0006666041,0.0008977166,0.0003637549,0.0008713914,0.001507093,0.001313318,0.001012172],"category_scores_gemma":[0.004818061,0.0004825389,0.0007538918,0.000988692,0.001087477,0.003467013,0.001546655,0.001738077,0.0003565491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00131094,"about_ca_system_score_gemma":0.0009047127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003088978,"about_ca_topic_score_gemma":0.002224744,"domain_scores_codex":[0.9996006,0.0001245819,0.00002203021,0.0001024231,0.0001171393,0.00003320941],"domain_scores_gemma":[0.9982193,0.0009867217,0.000265303,0.0003805193,0.00009885221,0.00004925936],"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":[0.00008712381,0.0001495329,0.001406525,0.0001048919,0.0001017075,0.00006201876,0.00006785986,0.8614544,0.009155631,0.008880512,0.000466857,0.118063],"study_design_scores_gemma":[0.000002492259,0.00002453509,0.0001866155,0.000002186785,0.000005449396,0.000006427563,0.000005559325,0.9866855,0.002640532,0.01026619,0.000169888,0.000004674114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0760434,0.000323595,0.9208696,0.0005146379,0.00002976138,0.00005939074,0.0000912618,0.001258473,0.0008098826],"genre_scores_gemma":[0.8079393,0.0004275783,0.1899273,0.0001739972,0.00006707665,0.0001100107,0.0003341522,0.00008411459,0.0009365422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003088978,"threshold_uncertainty_score":0.00951159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03237088785358007,"score_gpt":0.2991292460933815,"score_spread":0.2667583582398014,"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."}}