{"id":"W2091311489","doi":"10.1002/pmic.200401033","title":"A proteomic tool for protein identification from tandem mass spectral data","year":2005,"lang":"en","type":"article","venue":"PROTEOMICS","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Tandem mass spectrometry; Identification (biology); Tandem; Mass spectrometry; Contiguity; Ranking (information retrieval); Proteomics; Computational biology; Chemistry; Chromatography; Computer science; Biology; Artificial intelligence; Biochemistry; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002996968,0.0002745193,0.0002555482,0.00004343583,0.0002384915,0.0001441781,0.001139903,0.0002236008,0.0002104794],"category_scores_gemma":[0.0001493429,0.0002947364,0.00009220635,0.0001114579,0.0000694893,0.0004790329,0.0001980324,0.0003165487,0.00007388506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002297462,"about_ca_system_score_gemma":0.0001107771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002814,"about_ca_topic_score_gemma":0.000009715262,"domain_scores_codex":[0.9979239,0.00001235743,0.0006014315,0.000856347,0.0001956955,0.0004102919],"domain_scores_gemma":[0.997662,0.00002869664,0.0003658578,0.001758944,0.00009855084,0.00008596409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006853892,0.00008313927,0.0002525875,0.00004713618,0.00002609386,3.544791e-7,0.00003213308,0.00004816449,0.9901008,0.003042875,0.0003612599,0.005936901],"study_design_scores_gemma":[0.0006110847,0.00001419279,0.00004722896,0.00004772223,0.00002854723,0.000002291228,0.00001144171,0.01853605,0.9160257,0.04843088,0.01586996,0.0003749095],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3788785,0.00004024864,0.6149476,0.001023624,0.00001893062,0.00318762,0.001150556,0.0003623388,0.0003905162],"genre_scores_gemma":[0.2662896,0.00002414356,0.7243849,0.00005644125,0.0007579126,0.005914248,0.001236403,0.0000712204,0.001265095],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1125889,"threshold_uncertainty_score":0.9999505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02784043866749697,"score_gpt":0.2976543078436687,"score_spread":0.2698138691761717,"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."}}