{"id":"W2782354730","doi":"10.1126/science.aar3920","title":"The genomics of climate change","year":2018,"lang":"en","type":"letter","venue":"Science","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Genomics; Climate change; Adaptation (eye); Climate change adaptation; Computational biology; Biology; Evolutionary biology; Geography; Environmental resource management; Ecology; Genome; Genetics; Gene; Environmental science; Neuroscience","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":[0.001707169,0.0002819018,0.0004545626,0.0002725982,0.001650121,0.001203899,0.0005191408,0.008406214,0.00359309],"category_scores_gemma":[0.009521037,0.0002032659,0.0002581811,0.0002367411,0.001633662,0.001381081,0.0012028,0.01184877,0.001653878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001185517,"about_ca_system_score_gemma":0.0009399949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002918645,"about_ca_topic_score_gemma":0.005165145,"domain_scores_codex":[0.9992114,0.0002483729,0.00004370237,0.0001304698,0.0002259215,0.0001400732],"domain_scores_gemma":[0.9946789,0.003196141,0.0003016924,0.0002984171,0.0005621379,0.0009627778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001846296,0.00008345952,0.006640223,0.00007992744,0.00004346868,0.001900767,0.0006688972,0.0001599108,0.002510188,0.005117232,0.9129552,0.06965616],"study_design_scores_gemma":[0.00009136289,0.00009806202,0.01066687,0.0001275309,0.00003342985,0.001235479,0.0008324408,0.0003421245,0.0008093737,0.01954363,0.9661873,0.00003239375],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.005491238,0.003451966,0.0004409794,0.9652471,0.02014994,0.0000108295,0.000125196,0.00004602088,0.005036753],"genre_scores_gemma":[0.05625791,0.003764836,0.0005447551,0.8727987,0.05445997,0.00004609855,0.0001229492,0.00004218445,0.01196271],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.008406214,"threshold_uncertainty_score":0.01202005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04095623098240591,"score_gpt":0.2589943669404349,"score_spread":0.218038135958029,"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."}}