{"id":"W2011751385","doi":"10.1109/vast.2009.5333895","title":"MassVis: Visual analysis of protein complexes using mass spectrometry","year":2009,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Scatter plot; Computer science; Workflow; Plot (graphics); Visualization; Cluster analysis; Data visualization; Function (biology); Data mining; Mass spectrometry; Tandem mass spectrometry; Biological system; Information retrieval; Chemistry; Database; Artificial intelligence; Machine learning; Biology; Mathematics; Chromatography","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":[0.001632571,0.001405426,0.0007915044,0.004817768,0.0005430559,0.002397285,0.001376548,0.0008287616,0.01628462],"category_scores_gemma":[0.002565516,0.0006022166,0.0008968436,0.001643186,0.0004076621,0.002096572,0.002295761,0.00131916,0.002897614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005310198,"about_ca_system_score_gemma":0.0006481928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001337679,"about_ca_topic_score_gemma":0.001351793,"domain_scores_codex":[0.9995311,0.00009887551,0.00004694927,0.00007373116,0.0001984034,0.00005087084],"domain_scores_gemma":[0.9990853,0.0004495047,0.00009809129,0.000108514,0.0001622275,0.00009631713],"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":[0.003692935,0.0004556802,0.01067216,0.002634418,0.0006896494,0.001585375,0.003058123,0.01409738,0.3329656,0.03084666,0.1681036,0.4311985],"study_design_scores_gemma":[0.0006257984,0.0003999747,0.01962543,0.0004303824,0.0001657835,0.002491642,0.001389968,0.5117621,0.2368485,0.05698954,0.1688802,0.0003906288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0522834,0.0009280128,0.7773344,0.001042404,0.0002507945,0.0005526377,0.01299381,0.1475727,0.007041791],"genre_scores_gemma":[0.1745691,0.00105465,0.8009523,0.0003244734,0.0001186097,0.0008586823,0.008174029,0.009419059,0.004529078],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01628462,"threshold_uncertainty_score":0.05447745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03051407900671463,"score_gpt":0.3333892834232682,"score_spread":0.3028752044165536,"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."}}