{"id":"W4297164575","doi":"","title":"Rethinking wastewater characterization methods: a position paper","year":2012,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"EnviroSim (Canada)","funders":"","keywords":"Characterization (materials science); Position (finance); Wastewater; Computer science; Position paper; Environmental science; Environmental engineering; Business; Materials science; World Wide Web; Nanotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008211505,0.0003297351,0.0003483387,0.00009990242,0.0003860694,0.0003768388,0.0007806962,0.0003408068,0.000885234],"category_scores_gemma":[0.0003565758,0.0003234458,0.0002333511,0.0002785771,0.0001779614,0.0003892442,0.001655886,0.0005971115,0.0002681441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002563822,"about_ca_system_score_gemma":0.00002753968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001844842,"about_ca_topic_score_gemma":0.00007269242,"domain_scores_codex":[0.9896616,0.008179568,0.0005349776,0.0007281517,0.0004881106,0.0004075617],"domain_scores_gemma":[0.9971582,0.0004037112,0.0004781876,0.001549057,0.0002211524,0.0001896455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001167474,0.0005341722,0.006181603,0.0001468381,0.0001386013,0.00000334768,0.04418807,0.0001413335,0.8801281,0.002793825,0.000245981,0.06548646],"study_design_scores_gemma":[0.0003233299,3.586441e-7,0.02316783,0.001404209,0.0002458588,0.00001092389,0.0001052272,0.005950319,0.940806,0.01261635,0.01441059,0.0009589787],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7910398,0.000142533,0.1824232,0.01251984,0.0005065103,0.0003651824,0.0000440368,0.0003271275,0.01263183],"genre_scores_gemma":[0.860498,0.0001260939,0.129469,0.0001264334,0.00008727382,0.00006479055,0.001168319,0.00005256842,0.008407528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06945822,"threshold_uncertainty_score":0.9999217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02423562376702462,"score_gpt":0.2608134712529617,"score_spread":0.236577847485937,"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."}}