{"id":"W1984709499","doi":"10.1016/j.jprot.2014.03.035","title":"2DE: The Phoenix of Proteomics","year":2014,"lang":"en","type":"review","venue":"Journal of Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":136,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Proteome; Computational biology; Proteomics; Shotgun proteomics; Shotgun; Computer science; Data science; Proteogenomics; Posttranslational modification; Mass spectrometry; Focus (optics); Biology; Chemistry; Bioinformatics; Chromatography; Genomics; Biochemistry; Physics; Genome","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001525054,0.002280253,0.002229495,0.002733753,0.0005802318,0.002979939,0.002180493,0.002500796,0.01991302],"category_scores_gemma":[0.001445484,0.001006779,0.0008142379,0.003594221,0.00133933,0.004809038,0.003277226,0.005501363,0.02705031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008163354,"about_ca_system_score_gemma":0.001487422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002820147,"about_ca_topic_score_gemma":0.0004346817,"domain_scores_codex":[0.999382,0.00007170405,0.00005350805,0.0001055133,0.0002912412,0.00009595977],"domain_scores_gemma":[0.9993184,0.0001734071,0.0001167015,0.00007611277,0.0001742632,0.0001411505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007265405,0.00005462532,0.00007853663,0.004451632,0.00004777149,0.0001266664,0.00003240155,0.0004563819,0.005648792,0.01895376,0.1516005,0.8184764],"study_design_scores_gemma":[0.0000104,0.00002490688,0.00009732179,0.0003905608,0.00001460567,0.0002886491,0.000007363879,0.0001545142,0.001880627,0.003518025,0.9935988,0.0000141316],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004913427,0.9164164,0.0271488,0.003973915,0.01444266,0.00009636207,0.000581401,0.001398869,0.03545026],"genre_scores_gemma":[0.004088385,0.9157377,0.01965508,0.004819329,0.006356351,0.0001539157,0.001314225,0.0004730493,0.04740196],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01991302,"threshold_uncertainty_score":0.0666157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03185584465843334,"score_gpt":0.3441537277337659,"score_spread":0.3122978830753326,"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."}}