{"id":"W4253191610","doi":"10.1515/iupac.85.0736","title":"Shotgun Proteomics","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Chemical nomenclature; Terminology; Mass spectrometry; Chemistry; Standardization; Analytical Chemistry (journal); Computer science; Environmental chemistry; Chromatography; Organic chemistry","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":[0.003149021,0.001890507,0.001843328,0.006260423,0.001503818,0.004380643,0.003124103,0.001811061,0.0620181],"category_scores_gemma":[0.01228855,0.0008236638,0.001566933,0.01011009,0.0005166885,0.002604134,0.002996536,0.002252688,0.1297209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002314512,"about_ca_system_score_gemma":0.004617681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01010448,"about_ca_topic_score_gemma":0.01782564,"domain_scores_codex":[0.9966856,0.00043991,0.0005738493,0.0008625074,0.001113793,0.0003244275],"domain_scores_gemma":[0.995329,0.001097931,0.0005834539,0.001356437,0.001348333,0.0002848404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001439746,0.00002328387,0.001024768,0.002305927,0.00007739336,0.00004381658,0.00004192027,0.0002106337,0.0008798639,0.00143519,0.9810002,0.0128131],"study_design_scores_gemma":[0.00007013575,0.0000142522,0.002943302,0.0005648986,0.00004655094,0.0000960672,0.00005193965,0.0001734978,0.001004657,0.002350558,0.9926504,0.0000336776],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001763087,0.0004070466,0.0006673784,0.0001219132,0.00006957675,0.00003613635,0.9956209,0.001183913,0.001716811],"genre_scores_gemma":[0.0002593396,0.0003236291,0.001161084,0.00009307361,0.000008487668,0.0001157323,0.9970385,0.0001752163,0.0008249551],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0620181,"threshold_uncertainty_score":0.2074712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129957108510813,"score_gpt":0.3959863647262577,"score_spread":0.3829906538751764,"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."}}