{"id":"W2320416228","doi":"10.1109/tcbb.2015.2389813","title":"NovoExD: <italic>De novo</italic> Peptide Sequencing for ETD/ECD Spectra","year":2015,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Foundation","keywords":"Biology","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":[0.001704143,0.001883244,0.001145352,0.0014932,0.0008910733,0.002349282,0.002747818,0.001217701,0.13692],"category_scores_gemma":[0.005200558,0.001335449,0.001619085,0.001528693,0.0006782119,0.002002371,0.002132725,0.002615937,0.09051318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051114,"about_ca_system_score_gemma":0.001417752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002886124,"about_ca_topic_score_gemma":0.003554219,"domain_scores_codex":[0.9988872,0.0001245408,0.0001464872,0.000391086,0.0003632989,0.00008735002],"domain_scores_gemma":[0.9981389,0.0005484442,0.0001795391,0.000574531,0.0004125212,0.0001460818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001195487,0.0001573838,0.002036794,0.001884859,0.0002217208,0.000885756,0.0002560015,0.01169827,0.06353106,0.03516439,0.5055475,0.3774207],"study_design_scores_gemma":[0.0003150871,0.00008316824,0.001286513,0.0001587573,0.00004509299,0.000835586,0.00005625277,0.06762762,0.07830406,0.01531909,0.8358507,0.0001180977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006735204,0.001208209,0.752442,0.0008670267,0.001392099,0.0007076344,0.03835999,0.1401294,0.05815839],"genre_scores_gemma":[0.042545,0.001272378,0.7812777,0.0008469613,0.0001943727,0.0008115296,0.07623937,0.04787599,0.04893673],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.13692,"threshold_uncertainty_score":0.4580429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03292898694230986,"score_gpt":0.2919675063526077,"score_spread":0.2590385194102979,"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."}}