{"id":"W6977141016","doi":"10.6084/m9.figshare.20422187.v1","title":"Copper hydrophytoremediation by wetland macrophytes in semi-hydroponic and hydroponic mesocosms","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Macrophyte; Bioconcentration; Wetland; Mesocosm; Phytoremediation; Aquatic plant; Soil water; Water quality; Biomass (ecology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002224762,0.0002742512,0.0003241551,0.00009014481,0.0003323279,0.0002827734,0.0002634831,0.0002273685,0.0005178223],"category_scores_gemma":[0.0002095034,0.0001321858,0.0002283497,0.0001005943,0.0002467468,0.0003114209,0.0003752162,0.0004356243,0.0001192548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007079125,"about_ca_system_score_gemma":0.0007885679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02204842,"about_ca_topic_score_gemma":0.04196934,"domain_scores_codex":[0.9998142,0.00002342285,0.0000123025,0.00008477118,0.00003335392,0.00003192131],"domain_scores_gemma":[0.9997314,0.00004628915,0.0000500422,0.00002098786,0.00004625455,0.0001050817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005015099,0.0000736657,0.00327455,0.0000514908,0.000008414255,0.00005621985,0.0001370776,0.0001171025,0.9939122,0.00002534619,0.00004495174,0.001797528],"study_design_scores_gemma":[0.000254782,0.007200397,0.3054532,0.00003289728,0.0001301026,0.0002773016,0.001170332,0.007437842,0.6725166,0.0001747662,0.005289581,0.00006213778],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9992399,0.00006553173,0.0002535833,0.00002197183,0.000007334893,0.00002249129,0.0001033725,0.00001250033,0.0002732745],"genre_scores_gemma":[0.9944416,0.0001958988,0.00284678,0.00006778565,0.00001025738,0.0001164021,0.0004045204,0.000008690294,0.001907993],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.02204842,"threshold_uncertainty_score":0.04384017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01008070040702056,"score_gpt":0.2459852072839127,"score_spread":0.2359045068768922,"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."}}