{"id":"W4413902460","doi":"10.1021/acs.est.5c03102","title":"Broad-Scale Analysis of Factors Influencing Inputs of Domestic Wastewater Constituents from Onsite Wastewater Treatment Systems to Streams","year":2025,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Environment and Climate Change Canada; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de l’Environnement, de la Protection de la nature et des Parcs; Environment and Climate Change Canada","keywords":"STREAMS; Wastewater; Environmental science; Scale (ratio); Sewage treatment; Waste management; Environmental engineering; Engineering; Computer science; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002964968,0.0002081737,0.0002215496,0.0005859759,0.0003839909,0.0006473418,0.0001529606,0.0001340079,0.0003356034],"category_scores_gemma":[0.0008217056,0.0001004757,0.000211236,0.001008842,0.0003402823,0.0001713353,0.0002732818,0.0001466237,0.0000506567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00323475,"about_ca_system_score_gemma":0.002614405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3793351,"about_ca_topic_score_gemma":0.5974028,"domain_scores_codex":[0.9996779,0.00006180134,0.00001565497,0.00007038724,0.0001164203,0.0000578552],"domain_scores_gemma":[0.9995587,0.00008762315,0.0001397823,0.00001309109,0.0001549661,0.00004571641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001147352,0.00005881948,0.9686326,0.00005757969,0.00005151211,0.00008926975,0.0004232451,0.001077897,0.01782457,0.00004676867,0.00008882755,0.0115343],"study_design_scores_gemma":[0.000001511735,0.00003416181,0.9981572,0.000002291433,0.00001015303,0.000009900695,0.0002854347,0.0003957698,0.0008720942,0.00001423111,0.0002154319,0.000001791884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991666,0.00003199637,0.0002263075,0.000006898108,4.220758e-7,0.00001829131,0.0002035593,0.000004022821,0.0003418965],"genre_scores_gemma":[0.9985726,0.000118463,0.0004561161,0.00001145469,0.000001161234,0.00001333607,0.0003921726,0.000002468602,0.0004322532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3793351,"threshold_uncertainty_score":0.7542543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009035169069972978,"score_gpt":0.2567802375648308,"score_spread":0.2477450684948578,"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."}}