{"id":"W2001477533","doi":"10.1145/1389095.1389150","title":"Evolution of discrete gene regulatory models","year":2008,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Boolean network; Gene regulatory network; Attractor; Computer science; Crossover; Graph; Entropy (arrow of time); Random graph; Boolean function; Gene; Theoretical computer science; Topology (electrical circuits); Mathematics; Biology; Genetics; Algorithm; Artificial intelligence; Physics; Gene expression; Combinatorics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008035708,0.0004733406,0.0006761599,0.0007732566,0.0004037547,0.001133117,0.001207183,0.001139755,0.002711958],"category_scores_gemma":[0.003969452,0.0003342149,0.0007834981,0.0005305277,0.001115986,0.0008880224,0.0007629723,0.0009490416,0.0003359215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001811352,"about_ca_system_score_gemma":0.0004844072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003754914,"about_ca_topic_score_gemma":0.002008524,"domain_scores_codex":[0.9994849,0.0002020243,0.00002255459,0.0001228928,0.0001140143,0.00005366883],"domain_scores_gemma":[0.998893,0.0006818841,0.0001307394,0.0001103357,0.00009151,0.00009268649],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003681794,0.0000228479,0.000936407,0.00002572254,0.00002661794,0.0001238329,0.00009591669,0.8086631,0.002064488,0.1842959,0.0003522645,0.003355962],"study_design_scores_gemma":[0.00001734069,0.000008881744,0.0001327068,0.00000282532,0.000005583118,0.00002056453,0.00000810573,0.9602693,0.0002125652,0.03864808,0.0006689884,0.000005118688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4348397,0.0006726869,0.5329376,0.001482257,0.00009903947,0.00008826615,0.0006448519,0.0004102399,0.02882543],"genre_scores_gemma":[0.9374134,0.000376589,0.0504163,0.0001465711,0.00003209844,0.0001948843,0.0003938303,0.00008181224,0.01094456],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003754914,"threshold_uncertainty_score":0.01314235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012513431349652,"score_gpt":0.2084462078822069,"score_spread":0.1983210735687104,"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."}}