{"id":"W4367182092","doi":"10.1088/2632-2153/acc928","title":"Encrypted machine learning of molecular quantum properties","year":2023,"lang":"en","type":"article","venue":"Machine Learning Science and Technology","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto","funders":"","keywords":"Homomorphic encryption; Encryption; Computer science; Kernel (algebra); Theoretical computer science; Process (computing); Machine learning; Data mining; Artificial intelligence; Computer security; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001030029,0.0002537358,0.000456478,0.0002138979,0.000230983,0.0007346271,0.0009092076,0.000549601,0.002683105],"category_scores_gemma":[0.003783369,0.0001914979,0.0004513945,0.0002014412,0.0009490625,0.00217038,0.001010117,0.001263416,0.0005740175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007698635,"about_ca_system_score_gemma":0.0008041361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001097935,"about_ca_topic_score_gemma":0.0006044385,"domain_scores_codex":[0.9994056,0.0001952606,0.00002848088,0.00007947358,0.0002023882,0.00008875733],"domain_scores_gemma":[0.9984424,0.0006136622,0.0001277802,0.0005914093,0.0001840719,0.00004067696],"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":[0.0002669496,0.0001715415,0.00181249,0.00006224029,0.0000399911,0.0001484483,0.00008059778,0.8685875,0.013805,0.08550675,0.001365899,0.02815262],"study_design_scores_gemma":[0.000005100495,0.00001403036,0.00005646808,0.000002117437,0.000001626306,0.000007797929,0.000004001558,0.9835633,0.006918205,0.009227085,0.0001976113,0.000002706498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.372112,0.0001921725,0.6188228,0.0008138615,0.00008282436,0.00006054061,0.0002298407,0.002030467,0.005655491],"genre_scores_gemma":[0.9804469,0.00004772277,0.01804902,0.00005775216,0.000009911532,0.0000165439,0.00007761315,0.00004262042,0.00125173],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002683105,"threshold_uncertainty_score":0.008975863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01105112861753314,"score_gpt":0.2446731352432898,"score_spread":0.2336220066257566,"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."}}