{"id":"W2795198691","doi":"10.1126/science.359.6383.1480-e","title":"Genetic clines and climate change","year":2018,"lang":"en","type":"article","venue":"Science","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Evolutionary biology; Geography; Biology; Ecology; Environmental science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053308,0.000152098,0.0002395881,0.00115203,0.0004048483,0.001045982,0.0001536334,0.0003637459,0.00240003],"category_scores_gemma":[0.002460797,0.0001184344,0.000197318,0.00153217,0.0007576264,0.0003515774,0.0005927427,0.0005049206,0.0002019035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006551729,"about_ca_system_score_gemma":0.0003249001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01359601,"about_ca_topic_score_gemma":0.01951762,"domain_scores_codex":[0.9997088,0.00009258481,0.00001607852,0.0000823256,0.00004187501,0.00005827624],"domain_scores_gemma":[0.9991824,0.0002365733,0.000238201,0.00008530336,0.0001070633,0.0001504007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001054518,0.00003474538,0.9524038,0.00005993824,0.0003823449,0.000332592,0.0007371641,0.003605595,0.004274772,0.003305338,0.002910074,0.03184816],"study_design_scores_gemma":[0.000003993491,0.000009582793,0.9956689,0.00001026812,0.00001873656,0.00007036485,0.000181429,0.0006427889,0.00006071096,0.001439981,0.001884834,0.000008322047],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885323,0.001409794,0.0006703306,0.001021098,0.00005943403,0.000009907513,0.0007047651,0.00004860663,0.007543841],"genre_scores_gemma":[0.9987942,0.0004144138,0.0001337006,0.0001091833,0.00002204336,0.000004544373,0.0002236754,0.000007657635,0.0002904651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01359601,"threshold_uncertainty_score":0.02703375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0387962393275835,"score_gpt":0.3001734428165598,"score_spread":0.2613772034889763,"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."}}