{"id":"W2942866405","doi":"10.1186/s12859-019-2659-y","title":"IMMAN: an R/Bioconductor package for Interolog protein network reconstruction, mapping and mining analysis","year":2019,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Directorate for Biological Sciences; Institute for Research in Fundamental Sciences","keywords":"Benchmark (surveying); Bioconductor; Computer science; Network analysis; Protein–protein interaction; Biological network; Data mining; Computational biology; Biology; Machine learning; Theoretical computer science; Artificial intelligence; Genetics; Gene; Geography; Cartography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004800129,0.0002243071,0.0003128129,0.000111781,0.000131281,0.0001105533,0.0002034955,0.0002597072,0.00001990534],"category_scores_gemma":[0.0000319263,0.0002063441,0.0001567722,0.0002110425,0.00008029405,0.00003714292,0.0001347105,0.00009543638,0.0000107137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001393694,"about_ca_system_score_gemma":0.00005542689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000246237,"about_ca_topic_score_gemma":0.00004751457,"domain_scores_codex":[0.9986748,0.00002809045,0.0005868095,0.000233792,0.00008617062,0.0003903602],"domain_scores_gemma":[0.9989439,0.00002170088,0.0003191679,0.0004957633,0.00009564281,0.00012387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002431636,0.0004091649,0.5270987,0.00554437,0.01062544,0.000002671317,0.01204858,0.04847353,0.1199996,0.00807386,0.01654682,0.2487456],"study_design_scores_gemma":[0.003060337,0.001499861,0.006256284,0.0001425535,0.0004765564,0.00008345447,0.005577872,0.953168,0.00461978,0.001052647,0.02264188,0.001420735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7701499,0.0001591831,0.2280892,0.00002458278,0.0002427773,0.0007792165,0.00004098052,0.00002364235,0.0004905674],"genre_scores_gemma":[0.5471439,0.00004078391,0.4504279,0.0004514453,0.0004537887,0.00008104513,0.0007371921,0.00003368438,0.0006302658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9046945,"threshold_uncertainty_score":0.841447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0145027023044293,"score_gpt":0.227691884527975,"score_spread":0.2131891822235457,"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."}}