{"id":"W2576634470","doi":"10.1109/bibm.2016.7822520","title":"Optimal control for context-sensitive probabilistic Boolean networks with perturbation using probabilisitic model checking","year":2016,"lang":"en","type":"article","venue":"","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":"National Natural Science Foundation of China","keywords":"Reachability; Probabilistic logic; Computer science; Model checking; Context (archaeology); Optimal control; Computation; Theoretical computer science; Reachability problem; Mathematical optimization; Algorithm; Artificial intelligence; Mathematics","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":[0.002031114,0.0008904376,0.0007496261,0.0006281395,0.0004143483,0.001055746,0.001212294,0.0006462381,0.001549894],"category_scores_gemma":[0.007645461,0.0004477343,0.001138121,0.0004008905,0.001918523,0.001356943,0.001234721,0.001687457,0.0001188273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00199495,"about_ca_system_score_gemma":0.002475726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00746149,"about_ca_topic_score_gemma":0.006387228,"domain_scores_codex":[0.9984806,0.0004731379,0.00005318143,0.0002886659,0.0004915719,0.0002128453],"domain_scores_gemma":[0.9952825,0.003613254,0.0004759529,0.0002775311,0.0002640972,0.00008660548],"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":[0.00003885951,0.00001893885,0.0002902141,0.00002887956,0.00001606875,0.00003619001,0.00002215527,0.9725193,0.001669088,0.02177894,0.0000775939,0.003503858],"study_design_scores_gemma":[0.000006798627,0.00001048686,0.00002956351,0.000002541532,0.000005287707,0.000004032927,0.000002350381,0.9906584,0.0007274544,0.00847001,0.00008035964,0.000002671381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03070756,0.0000583315,0.9668049,0.0001418998,0.00001595764,0.00005827084,0.0000616713,0.0003583236,0.001793087],"genre_scores_gemma":[0.8976508,0.0001116777,0.1006212,0.00007335836,0.00001218372,0.0002042333,0.00009359628,0.0001002401,0.001132804],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00746149,"threshold_uncertainty_score":0.01483613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01256026662080994,"score_gpt":0.2266012482448214,"score_spread":0.2140409816240114,"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."}}