{"id":"W2100284033","doi":"10.1186/1471-2105-15-344","title":"CIG-P: Circular Interaction Graph for Proteomics","year":2014,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity Western University; Western University","funders":"Trinity Western University","keywords":"Visualization; Proteomics; Computer science; AKA; Computational biology; Graph; Data mining; Biology; Biochemistry; Theoretical computer science","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":[0.001172529,0.00245805,0.0008391365,0.003455206,0.0007331591,0.001846737,0.001975238,0.001324578,0.02473642],"category_scores_gemma":[0.004542539,0.001009417,0.002231767,0.002366224,0.0006561117,0.001816325,0.002359983,0.001691847,0.006197344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001023772,"about_ca_system_score_gemma":0.001378016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002774382,"about_ca_topic_score_gemma":0.002373897,"domain_scores_codex":[0.9992812,0.0001530243,0.00005342225,0.0001898218,0.0002681595,0.00005448588],"domain_scores_gemma":[0.9981803,0.001083617,0.000150625,0.0002681616,0.0002097531,0.0001075812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000770737,0.0002804093,0.004701916,0.004067644,0.000404891,0.001531056,0.0009002908,0.07903213,0.02680466,0.1381097,0.334677,0.4087196],"study_design_scores_gemma":[0.0002823137,0.0001595804,0.001728594,0.000403663,0.000134565,0.001267933,0.0001253351,0.3202901,0.01985911,0.2490711,0.4064831,0.00019457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00311877,0.0003970537,0.8787996,0.0005274444,0.0001443007,0.00026208,0.01446719,0.09853895,0.003744634],"genre_scores_gemma":[0.06394805,0.001457069,0.8493288,0.000766727,0.0001042401,0.00166797,0.057257,0.01996545,0.00550471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02473642,"threshold_uncertainty_score":0.08275163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01974616961840828,"score_gpt":0.2766336423122025,"score_spread":0.2568874726937942,"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."}}