{"id":"W4387823059","doi":"10.1038/s41576-023-00657-y","title":"Genomics for monitoring and understanding species responses to global climate change","year":2023,"lang":"en","type":"review","venue":"Nature Reviews Genetics","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":163,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Genomics; Climate change; Computational biology; Evolutionary biology; Ecology; Genetics; Genome; Gene","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006585987,0.0004889768,0.001257246,0.00006406527,0.0002379085,0.0001308371,0.000403919,0.000562855,0.00037445],"category_scores_gemma":[0.0002080999,0.0004073425,0.0003631778,0.0006934369,0.00008729758,0.00004817979,0.0006085239,0.0003264326,0.0007368266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002794992,"about_ca_system_score_gemma":0.00001859853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002639348,"about_ca_topic_score_gemma":0.00005123792,"domain_scores_codex":[0.9977834,0.00011952,0.0006061547,0.000639115,0.0002641839,0.0005875915],"domain_scores_gemma":[0.9988775,0.0001558847,0.0003020263,0.0004197359,0.00001261451,0.0002322897],"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":[0.00001698027,0.00002413417,0.0005625439,0.01586364,0.00004883319,0.000008275466,0.0001095256,2.607268e-7,0.000004833739,0.00280677,0.0116157,0.9689385],"study_design_scores_gemma":[0.00007077033,0.00004762512,0.0004208456,0.003466627,0.0003031496,0.00001388424,0.0001441063,8.609406e-7,0.000001181009,0.00007786357,0.9950494,0.0004036689],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003330705,0.993076,0.00005044881,0.0001040066,0.0008912956,0.002969523,0.001721726,0.00006426158,0.001089387],"genre_scores_gemma":[0.000004013208,0.9978136,0.0007076612,0.0001255492,0.00050775,0.0004904917,0.0001062937,0.00006093398,0.0001837523],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9834337,"threshold_uncertainty_score":0.9998378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3299978167777032,"score_gpt":0.4170931895875851,"score_spread":0.08709537280988189,"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."}}