{"id":"W2147087392","doi":"10.1093/nar/gkr1294","title":"MUSI: an integrated system for identifying multiple specificity from very large peptide or nucleic acid data sets","year":2011,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Biology; Computational biology; DNA microarray; Nucleic acid; Pipeline (software); Transcription (linguistics); Genetics; Bioinformatics; Computer science; Gene; Gene expression","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":[0.003379798,0.002842915,0.001812117,0.003623775,0.0009440657,0.001806928,0.002534871,0.001159958,0.008666189],"category_scores_gemma":[0.006033365,0.001610467,0.001861888,0.002201337,0.000769569,0.002365019,0.002878068,0.001980069,0.004212519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000913287,"about_ca_system_score_gemma":0.00143516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002106995,"about_ca_topic_score_gemma":0.003033821,"domain_scores_codex":[0.998593,0.0001958841,0.0001410392,0.0004977541,0.0004515584,0.0001207725],"domain_scores_gemma":[0.9976147,0.001117842,0.000323592,0.0004754009,0.0002524508,0.0002159822],"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":[0.006845765,0.0006756154,0.02862721,0.00262367,0.002766685,0.001187047,0.0009391457,0.013532,0.2376733,0.008830477,0.2162914,0.4800076],"study_design_scores_gemma":[0.0007536736,0.0008805973,0.03178196,0.0002005591,0.0004659206,0.001701978,0.0002600879,0.584481,0.2624903,0.02022529,0.09603127,0.0007274201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.02092831,0.0004253332,0.3953045,0.0003131044,0.0001491923,0.0004491377,0.02497669,0.5558484,0.001605335],"genre_scores_gemma":[0.08224928,0.0003891895,0.8353394,0.0006199085,0.0001074149,0.001621474,0.05964984,0.01705747,0.002966118],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008666189,"threshold_uncertainty_score":0.02899128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1474142261369567,"score_gpt":0.3545104690136365,"score_spread":0.2070962428766798,"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."}}