{"id":"W4322769977","doi":"10.3390/biom13030457","title":"Protein Design Using Physics Informed Neural Networks","year":2023,"lang":"en","type":"article","venue":"Biomolecules","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Israel Science Foundation","keywords":"Protein design; Computer science; Protein structure prediction; Robustness (evolution); Artificial neural network; Protein folding; Artificial intelligence; Sequence (biology); Machine learning; Protein structure; Physics; Chemistry","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":[0.0004957103,0.0005776566,0.000614754,0.0004427907,0.0003392517,0.0005847619,0.0007023089,0.0009497567,0.001287613],"category_scores_gemma":[0.001309,0.00045616,0.0004762995,0.0003637529,0.0006663806,0.0006711365,0.0007302006,0.0006704942,0.0002025859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00112781,"about_ca_system_score_gemma":0.001001358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003884824,"about_ca_topic_score_gemma":0.00412069,"domain_scores_codex":[0.9997999,0.00006191774,0.000007653564,0.00003698014,0.00007062756,0.00002285237],"domain_scores_gemma":[0.9996382,0.0002033785,0.00005442432,0.00002169486,0.00005851833,0.00002375485],"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":[0.00001434516,0.000009457101,0.00008898196,0.00001641586,0.00000625712,0.00001373269,0.000005726517,0.9902244,0.0006025051,0.004003467,0.0001248327,0.00488983],"study_design_scores_gemma":[0.000002831832,0.000004312481,0.00001222972,0.000001357487,9.715459e-7,0.000001645255,7.806806e-7,0.9978815,0.00008755399,0.00188598,0.000119961,9.032713e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08642224,0.0009329951,0.8962569,0.0007570988,0.00009052308,0.00009455007,0.00009735244,0.0004244498,0.01492393],"genre_scores_gemma":[0.799958,0.0005901696,0.1918883,0.00043299,0.00006213434,0.0003423234,0.0002330128,0.0001086517,0.006384502],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003884824,"threshold_uncertainty_score":0.008182883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02438450743216707,"score_gpt":0.2735235489733696,"score_spread":0.2491390415412025,"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."}}