{"id":"W2900855269","doi":"10.1016/j.aquabot.2018.11.004","title":"Demographic senescence in the aquatic plant Lemna gibba L. (Araceae)","year":2018,"lang":"en","type":"article","venue":"Aquatic Botany","topic":"Constructed Wetlands for Wastewater Treatment","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lemna gibba; Biology; Lemna; Senescence; Indeterminate growth; Fecundity; Frond; Population; Botany; Araceae; Zoology; Demography; Ecology; Macrophyte; Aquatic plant; Genetics","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":[0.0002069571,0.0001699173,0.000140593,0.0006290472,0.0002692606,0.0002526083,0.0003367556,0.0002564415,0.001321545],"category_scores_gemma":[0.0003881516,0.00008724787,0.0001147855,0.0002249337,0.0001857232,0.0003092787,0.0003242565,0.0002621074,0.0003757191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008109304,"about_ca_system_score_gemma":0.0001720651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006208028,"about_ca_topic_score_gemma":0.01004694,"domain_scores_codex":[0.9999523,0.00001711426,0.000002563087,0.0000139565,0.000005172939,0.000008916998],"domain_scores_gemma":[0.9997644,0.00006680463,0.0000594904,0.00001428121,0.00003288106,0.00006214299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001200913,0.0002480763,0.1965916,0.0002643588,0.00005063756,0.0004333678,0.001977466,0.001204476,0.7483884,0.001077897,0.0009203933,0.04764235],"study_design_scores_gemma":[0.00003689842,0.0006676055,0.9840687,0.0000165584,0.00002139879,0.0003132751,0.0009167167,0.002959452,0.00673897,0.0006172982,0.003611074,0.00003212737],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988532,0.0003024669,0.0001133737,0.00004393249,0.000001557168,0.000002386757,0.0001451345,0.00001296339,0.0005249687],"genre_scores_gemma":[0.9983174,0.00009996862,0.0001393467,0.00005818891,0.000002780921,0.00001032001,0.0002566967,0.000007887813,0.001107448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006208028,"threshold_uncertainty_score":0.01234382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01027905495525424,"score_gpt":0.2157207303978526,"score_spread":0.2054416754425983,"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."}}