{"id":"W4403157831","doi":"10.1016/j.scitotenv.2024.176754","title":"Willow traits outperform taxonomy in predicting phytoremediation services","year":2024,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Forest ecology and management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Espace pour la vie; Cégep Saint-Jean-sur-Richelieu; Université de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Willow; Phytoremediation; Taxonomy (biology); Biology; Environmental science; Botany; Ecology","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":[0.001657623,0.0005208584,0.0003483689,0.0007619819,0.0004866623,0.001508827,0.0002636993,0.0008548782,0.002208153],"category_scores_gemma":[0.00538692,0.0001244807,0.0004862279,0.0006280626,0.0003344864,0.001470007,0.0006528629,0.000524918,0.0007282878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004741824,"about_ca_system_score_gemma":0.0006490246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01277663,"about_ca_topic_score_gemma":0.03317114,"domain_scores_codex":[0.99966,0.0001107163,0.00002274627,0.00006941354,0.00005435513,0.00008278339],"domain_scores_gemma":[0.9961787,0.002145108,0.0005867986,0.0002046557,0.0003137981,0.0005710243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001477256,0.00004105052,0.9861071,0.00002026505,0.0001190077,0.00001974393,0.00008130685,0.002157677,0.001340695,0.0001485365,0.000235234,0.009581597],"study_design_scores_gemma":[0.00001107618,0.0002504731,0.9695043,0.00002178892,0.0001220551,0.00006779263,0.000457076,0.02618861,0.001196846,0.0009928374,0.001172815,0.0000142304],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978065,0.0001920291,0.0009296791,0.00007299495,0.000009815271,0.000003630006,0.0002326077,0.00002219288,0.0007306027],"genre_scores_gemma":[0.9985846,0.00006004677,0.0005816973,0.00002412094,0.000005522978,0.000001380814,0.0003100563,0.000007300934,0.0004253832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01277663,"threshold_uncertainty_score":0.02540457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006688843673122774,"score_gpt":0.1828837336976779,"score_spread":0.1761948900245551,"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."}}