{"id":"W2981738921","doi":"10.1002/wdev.364","title":"The benefits differential equations bring to limb development","year":2019,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Developmental Biology","topic":"Developmental Biology and Gene Regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Carleton University","funders":"","keywords":"Robustness (evolution); Limb development; Variety (cybernetics); Biology; Organogenesis; Vertebrate; Gene regulatory network; Computational biology; Computer science; Systems biology; Gene; Gene expression; Artificial intelligence; Genetics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007116306,0.001013334,0.001731301,0.0002312115,0.0008404131,0.00008287936,0.001273016,0.000805481,0.000090945],"category_scores_gemma":[0.0001337049,0.0006709788,0.0006778148,0.0003684639,0.0001982994,0.00001060579,0.003840903,0.0004077239,0.003422194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003260544,"about_ca_system_score_gemma":0.0007393179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001405128,"about_ca_topic_score_gemma":0.0001127988,"domain_scores_codex":[0.9951964,0.0005217292,0.001884931,0.001359152,0.0001660657,0.0008717316],"domain_scores_gemma":[0.998166,0.000162395,0.0006427182,0.0007146979,0.00007995923,0.0002342193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000462866,0.00005396854,0.00003869653,0.0009972254,0.0003906128,0.000001080175,0.000120037,0.000001319743,0.0003147733,0.00008059345,0.004896091,0.9930593],"study_design_scores_gemma":[0.0001685459,0.0002593221,0.00007372464,0.003971926,0.0001463942,0.0001035764,0.0000393501,0.000001274876,0.0002345135,0.00001466919,0.9940727,0.0009139834],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003385651,0.9927973,0.001050092,0.00006538494,0.001977399,0.002802446,0.00007614384,0.00003415441,0.0008585128],"genre_scores_gemma":[0.0001638491,0.9863883,0.001900397,0.0001542824,0.0004078364,0.001018608,0.005316326,0.00009136312,0.004559017],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9921454,"threshold_uncertainty_score":0.9995741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06685007593456252,"score_gpt":0.3602987803338935,"score_spread":0.2934487043993309,"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."}}