{"id":"W2991687158","doi":"10.3233/jid-2007-11305","title":"DESIGN AND IMPLEMENTATION OF A GENE NETWORK REVERSE ENGINEERING METHOD BASED ON MUTUAL INFORMATION","year":2007,"lang":"en","type":"article","venue":"Journal of Integrated Design and Process Science","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Reverse engineering; Computer science; Systems engineering; Engineering; Programming language","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":[0.003293596,0.00008609146,0.0001229438,0.0001885152,0.00006208694,0.00003158587,0.0001095415,0.00004921492,0.000003421138],"category_scores_gemma":[0.0001015016,0.00006658071,0.00002608203,0.0004821667,0.00006368506,0.00003777556,0.000009300986,0.00007153642,1.075878e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001968237,"about_ca_system_score_gemma":0.0002889075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003021479,"about_ca_topic_score_gemma":7.330833e-7,"domain_scores_codex":[0.9991565,0.00005249492,0.0003230591,0.00009726721,0.0002212635,0.0001493591],"domain_scores_gemma":[0.9990664,0.00004732865,0.0003006078,0.00006730982,0.0004322295,0.00008614425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003283375,0.00001133488,0.0005512714,0.0000206605,0.00002787606,0.000001865013,0.0002186834,0.6052423,0.374137,0.00001365604,0.000120965,0.01932609],"study_design_scores_gemma":[0.0004215259,0.0006769359,0.0008074888,0.0000425276,0.000038131,0.00004601696,0.0003731443,0.249211,0.7481121,0.00003092762,0.0001496236,0.00009059175],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.189659,0.0001613383,0.8100443,0.00001442492,0.00003361201,0.00007921896,5.497558e-7,0.000001569978,0.000006060538],"genre_scores_gemma":[0.7682577,0.00003900759,0.2315831,0.00007643456,0.00003534791,0.000001018581,0.000002377582,0.000003139604,0.000001875557],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5785987,"threshold_uncertainty_score":0.2715082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009852663611013486,"score_gpt":0.284954313781639,"score_spread":0.2751016501706255,"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."}}