{"id":"W1790014090","doi":"10.5555/arwg.15.4.hn3076665801k728","title":"Water-pollution study based on the physico-chemical and microbiological parameters of the Semenyih River, Selangor, Malaysia","year":2012,"lang":"en","type":"article","venue":"Arab world geographer","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Pollution; Water quality; Fishing; Water resource management; Contamination; Fecal coliform; Sampling (signal processing); Water pollution; Recreation; Hydrology (agriculture); Coliform bacteria; Geography; Fishery; Ecology; Biology; Bacteria","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":[0.0002719461,0.0004042891,0.0002386384,0.0008367216,0.0004103015,0.0005323427,0.0001474495,0.0002449403,0.0003580668],"category_scores_gemma":[0.0002359396,0.0002094974,0.0002890991,0.0007744764,0.0002557644,0.0002951749,0.0002832443,0.0001936458,0.000150598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003795855,"about_ca_system_score_gemma":0.000551535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01022342,"about_ca_topic_score_gemma":0.01522322,"domain_scores_codex":[0.9998291,0.00002902642,0.00002114968,0.00004620858,0.00005177169,0.00002285812],"domain_scores_gemma":[0.9998423,0.00001573402,0.00005051359,0.00000827806,0.00005231187,0.00003075931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003342835,0.0003698833,0.9185866,0.0001013957,0.0001174219,0.0005199515,0.00149225,0.0007849735,0.06748714,0.0001257004,0.0001562056,0.009924263],"study_design_scores_gemma":[0.000008840458,0.0005806606,0.9801155,0.00001494876,0.00004918938,0.0004261831,0.001399497,0.001726923,0.014688,0.00005190937,0.0009204861,0.00001791326],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994063,0.00003870451,0.0001472025,0.000005786323,0.000001178387,0.000007905873,0.000108691,0.000002291528,0.0002819217],"genre_scores_gemma":[0.9985845,0.00007261759,0.0003946382,0.00001358925,0.000001747343,0.00001412188,0.0002720202,0.000001690844,0.000645039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01022342,"threshold_uncertainty_score":0.02032781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01818904610626267,"score_gpt":0.2349617290035171,"score_spread":0.2167726828972544,"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."}}