{"id":"W4381164011","doi":"10.56946/jce.v2i01.135","title":"Characterization of Paper Mill Effluent and Its Impacts on the Environment","year":2023,"lang":"en","type":"article","venue":"Journal of Chemistry and Environment","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Rajshahi University","keywords":"Effluent; Pollutant; Pollution; Environmental science; Paper mill; Water quality; Pulp and paper industry; Environmental engineering; Chemistry; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000241664,0.0003323187,0.0002730846,0.0007748935,0.0003788128,0.0007975287,0.000206076,0.0005643922,0.00140049],"category_scores_gemma":[0.0002463423,0.00008894935,0.0003250213,0.0009335841,0.0001477618,0.0003892603,0.0002243212,0.0003506729,0.0002685778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002318384,"about_ca_system_score_gemma":0.0003080636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002420312,"about_ca_topic_score_gemma":0.004085182,"domain_scores_codex":[0.9996876,0.00002449321,0.00002200437,0.0000499227,0.0001751273,0.00004083542],"domain_scores_gemma":[0.9998661,0.00002002235,0.00003330918,0.000006263756,0.00006040672,0.00001390526],"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":[0.0001516839,0.0001653832,0.02335553,0.0003366878,0.00002902116,0.0004307921,0.0002261166,0.0005880268,0.9538226,0.0001104128,0.0001514636,0.02063234],"study_design_scores_gemma":[0.00001627668,0.001065175,0.1822839,0.00006575694,0.00005795116,0.001076285,0.001782523,0.003071324,0.8000381,0.0003346636,0.01015691,0.0000510651],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920797,0.0005997881,0.003651836,0.00005186263,0.00001383756,0.00006053043,0.0006467918,0.00001782494,0.002877849],"genre_scores_gemma":[0.9847075,0.001184259,0.005411595,0.0001067213,0.00001188978,0.00006045697,0.0007488226,0.00001381375,0.007755042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002420312,"threshold_uncertainty_score":0.004812419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01514159765545625,"score_gpt":0.220665998227828,"score_spread":0.2055244005723717,"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."}}