{"id":"W3048608287","doi":"10.7554/elife.55778","title":"Geometric models for robust encoding of dynamical information into embryonic patterns","year":2020,"lang":"en","type":"article","venue":"eLife","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft; Simons Foundation","keywords":"Bifurcation; Function (biology); Segmentation; Biology; Dynamics (music); Encoding (memory); Dynamical systems theory; Topology (electrical circuits); Computer science; Evolutionary biology; Statistical physics; Physics; Artificial intelligence; Mathematics; Neuroscience; Combinatorics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001025847,0.00008281374,0.0001327879,0.00006690507,0.00003273102,0.00001074398,0.0001355895,0.00007726496,0.000005914383],"category_scores_gemma":[0.00008053485,0.00008337067,0.00012285,0.0002116336,0.00001519553,0.000009357432,0.00007682072,0.00003625121,0.000003817998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001268179,"about_ca_system_score_gemma":0.00003791643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006607041,"about_ca_topic_score_gemma":0.000007251084,"domain_scores_codex":[0.9993782,0.00001580923,0.0002117205,0.0001350627,0.0001302706,0.0001289034],"domain_scores_gemma":[0.9995513,0.000008807832,0.0001019228,0.00015205,0.0001107282,0.00007517634],"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":[0.000130195,0.00004527529,0.007550214,0.0003083882,0.0003159492,4.311962e-7,0.0003449588,0.8816931,0.08771251,0.0001909523,0.004861518,0.01684656],"study_design_scores_gemma":[0.0006683253,0.0002834187,0.001918892,0.00001300178,0.00008709054,0.000001419348,0.0001510192,0.8896548,0.1024287,0.00003714119,0.004506917,0.0002492697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5727977,0.0001685995,0.4266848,0.0001582909,0.00002757896,0.00008823527,0.00001320209,0.000006453984,0.00005509688],"genre_scores_gemma":[0.9958159,0.00008957916,0.003357921,0.0003117959,0.0001426232,0.00001287368,0.0002427471,0.000009129241,0.00001743031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4233269,"threshold_uncertainty_score":0.3399757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.016659695165046,"score_gpt":0.229914280251499,"score_spread":0.213254585086453,"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."}}