{"id":"W1530222056","doi":"10.5539/jsd.v8n3p28","title":"Water Quality Monitoring Using Biological Indicators in Cameron Highlands Malaysia","year":2015,"lang":"en","type":"article","venue":"Journal of Sustainable Development","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Invertebrate; Water quality; Environmental science; Sampling (signal processing); Abundance (ecology); Pollution; Hydrology (agriculture); Ecology; Biotic index; River pollution; Water resource management; Biology; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.000234544,0.0003194069,0.0000904964,0.0008226219,0.0002326562,0.0003133421,0.0001382992,0.0001372554,0.0002408736],"category_scores_gemma":[0.0002709065,0.000118497,0.00006535816,0.0007208013,0.0001866633,0.0002559862,0.0002019079,0.0001033452,0.00004553896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003503344,"about_ca_system_score_gemma":0.0004550885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0158289,"about_ca_topic_score_gemma":0.04377167,"domain_scores_codex":[0.9998791,0.00003992361,0.00001339379,0.00002126684,0.00002780825,0.00001856248],"domain_scores_gemma":[0.9998009,0.00002464449,0.0001043145,0.000005426734,0.0000402991,0.00002452539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007094591,0.00007532365,0.9548112,0.0001245415,0.00002138553,0.0005041335,0.0008081188,0.0005386079,0.01299519,0.00009702022,0.0002102052,0.02974334],"study_design_scores_gemma":[0.000002853958,0.0001559329,0.9933769,0.00003608562,0.00001456112,0.0002801022,0.001535456,0.0009988485,0.002919833,0.00003273629,0.0006383933,0.000008325591],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991437,0.0002265335,0.0001601817,0.00003258238,0.00000213584,0.00001218267,0.00007984325,0.000003633883,0.0003392267],"genre_scores_gemma":[0.9988189,0.0002413915,0.0006284838,0.000008357928,0.000001393404,0.00001124182,0.00006248291,4.410251e-7,0.0002272101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0158289,"threshold_uncertainty_score":0.03147352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07034095943387553,"score_gpt":0.3178040381700322,"score_spread":0.2474630787361566,"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."}}