{"id":"W4311890421","doi":"10.48084/etasr.5230","title":"Classification of Macromolecules Based on Amino Acid Sequences Using Deep Learning","year":2022,"lang":"en","type":"article","venue":"Engineering Technology & Applied Science Research","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Deep learning; Artificial intelligence; Computer science; Word2vec; Embedding; Word embedding; Task (project management); Machine learning; Convolutional neural network; Artificial neural network; Pattern recognition (psychology); Engineering","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":[0.0002413718,0.0006985288,0.000519484,0.001861027,0.0002706489,0.0008219735,0.0004650705,0.0007892554,0.002096468],"category_scores_gemma":[0.000564931,0.0002151426,0.0007051606,0.0009625205,0.0002365827,0.0009455515,0.0004445821,0.0006072932,0.00147079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006480248,"about_ca_system_score_gemma":0.0004006812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001935256,"about_ca_topic_score_gemma":0.001810358,"domain_scores_codex":[0.9998592,0.00001346794,0.00001061767,0.00004089443,0.0000489741,0.00002678809],"domain_scores_gemma":[0.9997256,0.00005709142,0.00006913637,0.00002419811,0.00009221389,0.00003170563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00103913,0.0004451557,0.01701166,0.0006211994,0.0001618764,0.0005506598,0.0001258702,0.09862121,0.2842797,0.005794419,0.005931988,0.5854172],"study_design_scores_gemma":[0.00001151454,0.0001188496,0.00457354,0.00002992145,0.0000308501,0.0001496876,0.00005030133,0.9280482,0.05916882,0.004321902,0.003474581,0.00002186561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5134277,0.004414902,0.4675457,0.0006407403,0.0002414356,0.000143377,0.001864052,0.004811083,0.00691091],"genre_scores_gemma":[0.8291801,0.002083509,0.1582685,0.0002071225,0.00007012986,0.0000872063,0.003064819,0.000112033,0.006926726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002096468,"threshold_uncertainty_score":0.007013381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02226822236046992,"score_gpt":0.3170238563315601,"score_spread":0.2947556339710902,"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."}}