{"id":"W4229055896","doi":"10.1073/pnas.2121249119","title":"Erratic spatiotemporal vegetation growth anomalies drive population outbreaks in a trans-Saharan insect migrant","year":2022,"lang":"en","type":"letter","venue":"Proceedings of the National Academy of Sciences","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ministerio de Universidades; Agencia Estatal de Investigación; Consejo Superior de Investigaciones Científicas; Government of Canada; Agència de Gestió d'Ajuts Universitaris i de Recerca; Generalitat de Catalunya; Ministerio de Ciencia e Innovación; National Geographic Society","keywords":"Outbreak; Vegetation (pathology); Geography; Insect; Population; Ecology; Biology; Environmental health; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002060788,0.0003120045,0.0003887856,0.0002637591,0.001619262,0.001367551,0.000527498,0.01035374,0.003116253],"category_scores_gemma":[0.008699747,0.0002298891,0.0002805422,0.0002746403,0.0008869214,0.0008817225,0.000600345,0.009576181,0.003111072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00125014,"about_ca_system_score_gemma":0.0008017198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009742451,"about_ca_topic_score_gemma":0.01543871,"domain_scores_codex":[0.9994577,0.0001886288,0.0000667024,0.0001078838,0.00008793414,0.00009114425],"domain_scores_gemma":[0.9960914,0.002192518,0.0003508275,0.0002170255,0.0007474483,0.0004006813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004381132,0.00009753872,0.01905904,0.00005649999,0.00007578718,0.006111964,0.0007009747,0.0001484597,0.001240768,0.002672843,0.9268752,0.04252292],"study_design_scores_gemma":[0.0005272059,0.0004022153,0.05282992,0.0003947272,0.0001881247,0.006197057,0.006345005,0.004886622,0.002277363,0.02920697,0.8965583,0.0001865201],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01055282,0.0008243791,0.0003738047,0.9691026,0.01269032,0.00001161136,0.0001918437,0.00005277322,0.006199887],"genre_scores_gemma":[0.1049929,0.001353584,0.0004992699,0.8565837,0.02099733,0.00003409757,0.000132427,0.00005045468,0.01535623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01035374,"threshold_uncertainty_score":0.01937145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02505904851932132,"score_gpt":0.2436070320766242,"score_spread":0.2185479835573029,"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."}}