{"id":"W229543366","doi":"","title":"Remote Sensing Time Series for Modeling Invasive Species Distribution: A Case Study of Tamarix spp. in the US and Mexico","year":2010,"lang":"en","type":"article","venue":"ScholarsArchive  (Brigham Young University)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Ontario Innovation Trust","keywords":"Tamarix; Habitat; Wetland; Riparian zone; Geography; Vegetation (pathology); Species distribution; Invasive species; Phenology; Ecology; Environmental science; Physical geography; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.000616385,0.0004058453,0.0001978708,0.0008494937,0.0003131966,0.0005083237,0.0005972138,0.0005748111,0.0005228853],"category_scores_gemma":[0.001233143,0.0001734303,0.0004210731,0.0007166301,0.0002101007,0.0004704361,0.0002988708,0.0003315583,0.00007027203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001074463,"about_ca_system_score_gemma":0.0004080834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1509618,"about_ca_topic_score_gemma":0.1380451,"domain_scores_codex":[0.9998952,0.00004028364,0.000006783463,0.00003088221,0.00001184142,0.0000150338],"domain_scores_gemma":[0.9994407,0.0003586099,0.00009594345,0.00003372966,0.00004756916,0.00002342413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001845544,0.0004089478,0.290321,0.00005201992,0.0001717474,0.000395223,0.0001800551,0.6864706,0.0008267809,0.00151069,0.001303784,0.01817455],"study_design_scores_gemma":[0.0000103723,0.00003770011,0.03394141,0.00000510922,0.00002348677,0.00002621068,0.0001213572,0.9651689,0.0001535979,0.0001730722,0.0003314076,0.000007314517],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959875,0.0001234669,0.002358113,0.0001973754,0.000007259777,0.00001645663,0.0006039416,0.00007224729,0.0006336715],"genre_scores_gemma":[0.9949114,0.0001291036,0.003964727,0.00001511011,0.00001008108,0.00002325251,0.0005633646,0.000008410859,0.0003746003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1509618,"threshold_uncertainty_score":0.3001662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02002297521897555,"score_gpt":0.2198829635409078,"score_spread":0.1998599883219322,"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."}}