{"id":"W2042330903","doi":"10.1016/j.jprot.2015.03.009","title":"Extracting high confidence protein interactions from affinity purification data: At the crossroads","year":2015,"lang":"en","type":"article","venue":"Journal of Proteomics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Computational biology; Computer science; Biology","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":[0.007523576,0.001549812,0.002134166,0.004863598,0.001067175,0.006138421,0.002936056,0.002037793,0.001498683],"category_scores_gemma":[0.03088814,0.0008916278,0.001438622,0.005382699,0.001198266,0.005982298,0.002674512,0.00400285,0.002473949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007017978,"about_ca_system_score_gemma":0.001749142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00126143,"about_ca_topic_score_gemma":0.003425107,"domain_scores_codex":[0.9938048,0.001917604,0.0005903158,0.001230188,0.002179309,0.0002778004],"domain_scores_gemma":[0.9670789,0.02427188,0.001933293,0.003700059,0.002429698,0.0005860873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001324073,0.001108865,0.09002882,0.004623965,0.001864561,0.001578563,0.0008812444,0.033567,0.1269663,0.03172812,0.03299667,0.6733319],"study_design_scores_gemma":[0.000107403,0.0003079217,0.05145135,0.0007610527,0.0007660663,0.003146668,0.0009890861,0.4828278,0.06801878,0.3364614,0.05493626,0.0002262693],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1190295,0.01642334,0.8410076,0.008550624,0.0003009923,0.0001784857,0.005467564,0.006557976,0.002483916],"genre_scores_gemma":[0.5135889,0.01058622,0.4505869,0.002224513,0.0008048289,0.0001502015,0.01955541,0.001102858,0.001400058],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007523576,"threshold_uncertainty_score":0.03978896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05452734530798296,"score_gpt":0.2988572754475983,"score_spread":0.2443299301396153,"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."}}