{"id":"W6968907457","doi":"10.5683/sp2/uvv4a0","title":"JProteomics2014","year":2020,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Profiling (computer programming); Computation; Proteomics; Proteogenomics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002887804,0.005781946,0.002561635,0.004437867,0.001926311,0.00332402,0.006101265,0.003253898,0.02485038],"category_scores_gemma":[0.00709308,0.001921221,0.003858228,0.00528993,0.0009822091,0.001930917,0.00376428,0.003360382,0.03702286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00227214,"about_ca_system_score_gemma":0.004180868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02489158,"about_ca_topic_score_gemma":0.04606543,"domain_scores_codex":[0.9978325,0.0003547616,0.0002099787,0.0007698464,0.0005797306,0.0002532129],"domain_scores_gemma":[0.9975562,0.0006173482,0.0001544956,0.001128547,0.0003582981,0.0001850623],"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":[0.0008611145,0.0002370632,0.002761177,0.002848418,0.0006327886,0.0002079113,0.0001232232,0.00629589,0.007900205,0.004826917,0.951471,0.02183429],"study_design_scores_gemma":[0.001464422,0.0001781664,0.01176252,0.000344292,0.0004182504,0.0004997501,0.0001072785,0.02232658,0.01262838,0.01907946,0.9309664,0.0002244323],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002026785,0.0004761204,0.00727689,0.000212301,0.0001105593,0.0001250306,0.9536697,0.03366477,0.002437851],"genre_scores_gemma":[0.002086522,0.0001297414,0.008714356,0.0001073177,0.00001075826,0.0002169037,0.9868579,0.001232644,0.0006437843],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9751496,"threshold_uncertainty_score":0.08313274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02348072278040518,"score_gpt":0.2671797914581044,"score_spread":0.2436990686776992,"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."}}