{"id":"W2138091633","doi":"10.7202/705152ar","title":"Biodegradable dissolved organic carbon removal during biological filtration on granular actived carbon","year":2005,"lang":"en","type":"article","venue":"Revue des sciences de l eau","topic":"Water Treatment and Disinfection","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Filtration (mathematics); Dissolved organic carbon; Pulp and paper industry; Adsorption; Biomass (ecology); Chemistry; Organic matter; Sand filter; Filter (signal processing); Water treatment; Environmental science; Environmental chemistry; Total organic carbon; Environmental engineering; Slow sand filter; Activated carbon; Carbon fibers; Chromatography; Wastewater; Ecology; Biology; Materials science; Organic chemistry; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002315217,0.0001452376,0.0001194761,0.00005207436,0.0004139057,0.00006557403,0.0001679302,0.00007683864,0.0001985702],"category_scores_gemma":[0.00003871863,0.000110014,0.00005172264,0.0004082557,0.0004558509,0.0002272455,0.0000473571,0.00007989398,0.00007103507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005622932,"about_ca_system_score_gemma":0.00001051348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001105602,"about_ca_topic_score_gemma":0.0008238234,"domain_scores_codex":[0.9988367,0.0000723101,0.0001384234,0.0004015467,0.0001886712,0.0003623296],"domain_scores_gemma":[0.9996832,0.0000236449,0.00006066525,0.0001502232,0.000004696265,0.00007754581],"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":[0.00004653322,0.0001802957,0.2482994,0.000007296774,0.000005441456,0.00002289169,0.0006938521,0.004085816,0.7447606,0.00003847702,0.00001026838,0.001849139],"study_design_scores_gemma":[0.0007176891,0.0007907119,0.4831307,0.00005872984,0.00003331164,0.0001860257,0.0001729276,0.05511175,0.4572991,0.001729479,0.0002861646,0.0004834608],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844044,0.00005484257,0.00005663036,0.000173522,0.0000734287,0.0001453282,9.929369e-7,0.00008257884,0.01500828],"genre_scores_gemma":[0.9975049,0.00004413216,0.001909266,0.00003220578,0.00008999992,0.000009960749,0.000004797949,0.000006821487,0.0003979036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2874615,"threshold_uncertainty_score":0.448624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04603838536290202,"score_gpt":0.2568671471062616,"score_spread":0.2108287617433596,"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."}}