{"id":"W3205203460","doi":"10.3934/math.2022066","title":"Branch prioritization motifs in biochemical networks with sharp activation","year":2021,"lang":"en","type":"article","venue":"AIMS Mathematics","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Prioritization; Kinetics; Mechanism (biology); Chemistry; Shut down; Computer science; Biophysics; Computational biology; Physics; Biology; Engineering","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":[0.0000821695,0.00009256184,0.0001004244,0.00002397482,0.00001998692,0.00001802896,0.0000495656,0.0001055578,0.0000128551],"category_scores_gemma":[0.0001102498,0.00008405753,0.00002247105,0.000184301,0.00001688178,0.000004246857,0.00002587879,0.00007264342,0.000002271307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001087568,"about_ca_system_score_gemma":0.0000335726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002174901,"about_ca_topic_score_gemma":0.000004057491,"domain_scores_codex":[0.9994542,0.00001235574,0.0001432671,0.0001975786,0.00006763822,0.0001249346],"domain_scores_gemma":[0.9996448,0.000003471014,0.00004230952,0.0002057382,0.00007223906,0.00003141536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008468916,0.00008814927,0.0001601415,0.00005330797,0.00001284534,0.000001013709,0.0000535345,0.002962508,0.9954629,0.0001667744,0.0004059431,0.0006244464],"study_design_scores_gemma":[0.0003258358,0.00003666309,0.0007330012,0.00008948836,0.000009477342,0.00004036912,0.00004005886,0.002376034,0.9941089,0.0001110952,0.001974804,0.0001542616],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8792809,0.0002456329,0.1199542,0.0001234645,0.00007702313,0.00009660651,0.000001728297,0.00001681558,0.0002036595],"genre_scores_gemma":[0.9898293,0.0001043152,0.009222812,0.00006348011,0.0002566515,0.000008455605,0.0001533406,0.00001882593,0.0003428366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1107314,"threshold_uncertainty_score":0.3427767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004617849261856808,"score_gpt":0.2008505749923469,"score_spread":0.1962327257304901,"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."}}