{"id":"W2953051190","doi":"10.1016/j.aquabot.2019.06.006","title":"World distribution, diversity and endemism of aquatic macrophytes","year":2019,"lang":"en","type":"article","venue":"Aquatic Botany","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":193,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"Oulun Yliopisto; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Consejo Nacional de Ciencia y Tecnología; Universität Wien; Universidade Estadual de Maringá; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Carnegie Trust for the Universities of Scotland; University of Glasgow; Department for Environment, Food and Rural Affairs, UK Government","keywords":"Macrophyte; Endemism; Diversity (politics); Distribution (mathematics); Ecology; Geography; Aquatic plant; Biology; Sociology; Anthropology; Mathematics","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":[0.0003748247,0.0001398077,0.00009459449,0.002240208,0.0002487964,0.0003795919,0.0001330235,0.0001480249,0.001838087],"category_scores_gemma":[0.0005157521,0.0001176877,0.0002665561,0.001562255,0.0003927855,0.0007387703,0.0003478931,0.0002084702,0.0002894003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002329779,"about_ca_system_score_gemma":0.0001176665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003587799,"about_ca_topic_score_gemma":0.006343308,"domain_scores_codex":[0.9998851,0.000023146,0.00001488365,0.00003754975,0.00001842872,0.00002082178],"domain_scores_gemma":[0.9991916,0.0001795636,0.0003443397,0.00006643018,0.0001101452,0.0001078594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002926828,0.00002741563,0.9665161,0.00007325933,0.0002365523,0.0001042898,0.0005520332,0.0006389551,0.004730505,0.001084889,0.0005906732,0.02515268],"study_design_scores_gemma":[0.000002756652,0.00004066178,0.9971878,0.0000115134,0.00002331185,0.000237506,0.0002330315,0.0003701293,0.0001821409,0.0002498516,0.001456356,0.000004937423],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933817,0.001299496,0.0002850039,0.00007191809,0.000004752369,0.000003193134,0.002356288,0.00001254876,0.002585129],"genre_scores_gemma":[0.9967859,0.0006523812,0.0003060908,0.00001292157,0.000005882744,0.000003451782,0.001671764,0.000003553957,0.0005580218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003587799,"threshold_uncertainty_score":0.007133842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006400983267498246,"score_gpt":0.1890314203369575,"score_spread":0.1826304370694592,"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."}}