{"id":"W4238246996","doi":"10.1023/a:1013908913162","title":"Liming of Acid and Metal Contaminated Catchments for the Improvement of Drainage Water Quality","year":2001,"lang":"en","type":"article","venue":"Water Air & Soil Pollution","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Wetland; Environmental science; Biota; Dolomite; Groundwater; Drainage basin; Drainage; Hydrology (agriculture); Surface water; Environmental chemistry; Environmental engineering; Ecology; Geology; Chemistry; Mineralogy; Biology; Geography","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":[0.0003823756,0.0001418336,0.0002324183,0.0003732199,0.0005186512,0.0004858977,0.0002960748,0.0002414696,0.001274536],"category_scores_gemma":[0.0007026772,0.0001028755,0.0002465498,0.0003939557,0.0002137241,0.0002289861,0.0003038461,0.0002200557,0.00009598308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002460414,"about_ca_system_score_gemma":0.0005926323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004483966,"about_ca_topic_score_gemma":0.01029764,"domain_scores_codex":[0.9998907,0.00003421289,0.00001144843,0.00001797978,0.00002596685,0.00001973104],"domain_scores_gemma":[0.9998108,0.00007090502,0.00002678801,0.00001480766,0.00003765845,0.00003912835],"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":[0.003604505,0.0006582208,0.03165925,0.0006449187,0.00008875589,0.0005115802,0.0005467469,0.006098469,0.856657,0.0007344893,0.0006869761,0.09810913],"study_design_scores_gemma":[0.0003821786,0.002104824,0.1793264,0.00008871203,0.0002549713,0.0005579085,0.001012745,0.01645935,0.7875952,0.001546932,0.01061882,0.00005197653],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964056,0.0002500414,0.002024638,0.00005677802,0.00001303947,0.00004246446,0.00004441393,0.00004476292,0.001118327],"genre_scores_gemma":[0.9951196,0.000225537,0.003456075,0.00003824424,0.000006094357,0.00001630454,0.00006652495,0.000008973429,0.001062629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004483966,"threshold_uncertainty_score":0.008915722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0130610746338221,"score_gpt":0.2435591647857896,"score_spread":0.2304980901519675,"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."}}