{"id":"W2158197251","doi":"10.1093/database/baq023","title":"iRefWeb: interactive analysis of consolidated protein interaction data and their supporting evidence","year":2010,"lang":"en","type":"article","venue":"Database","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":223,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"Computer science; Interface (matter); Interaction information; World Wide Web; Reliability (semiconductor); Database; Information retrieval","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":[0.01166786,0.003057122,0.002278672,0.02897572,0.00111399,0.006749505,0.003673158,0.001316768,0.0545336],"category_scores_gemma":[0.04280717,0.001560007,0.002718654,0.01664579,0.0006228758,0.00556478,0.005860539,0.002167293,0.01319047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001713,"about_ca_system_score_gemma":0.002392503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003204447,"about_ca_topic_score_gemma":0.00638058,"domain_scores_codex":[0.9965388,0.0007717073,0.000541476,0.0007560266,0.001210603,0.0001813798],"domain_scores_gemma":[0.9728127,0.01909615,0.001953113,0.00272751,0.002714304,0.0006961852],"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":[0.001869865,0.0003261748,0.0284364,0.01040083,0.003492018,0.002175142,0.00144825,0.006608113,0.01144169,0.01521746,0.5071344,0.4114496],"study_design_scores_gemma":[0.0009859995,0.0002563449,0.0443379,0.003264862,0.001903931,0.003610119,0.001228734,0.1228246,0.02291713,0.1082222,0.6897945,0.0006536784],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.01749026,0.004095854,0.3231945,0.001668197,0.0004180349,0.0008990081,0.3613145,0.2808303,0.01008927],"genre_scores_gemma":[0.05571553,0.002489782,0.5955222,0.0004222862,0.0002874119,0.002282067,0.3176264,0.02175834,0.003895898],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.0545336,"threshold_uncertainty_score":0.1824331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02602835155197479,"score_gpt":0.3164998662923536,"score_spread":0.2904715147403788,"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."}}