{"id":"W4381798696","doi":"10.3390/w15132325","title":"Drinking and Natural Mineral Water: Treatment and Quality–Safety Assurance","year":2023,"lang":"en","type":"article","venue":"Water","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scope (computer science); Sanitation; Legislation; Water quality; Water treatment; Human life; Hazard; Environmental planning; Environmental science; Quality assurance; Mineral water; Business; Waste management; Risk analysis (engineering); Water resource management; Environmental engineering; Engineering; Operations management; Computer science; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001408511,0.00009315741,0.00009973689,0.0000245841,0.0001056529,0.00003238698,0.00005985339,0.00003949707,0.0002024214],"category_scores_gemma":[0.000006715902,0.00004879615,0.00001525255,0.00004185436,0.0001174672,0.0001890487,0.0001602299,0.00004129611,0.00050221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003812942,"about_ca_system_score_gemma":6.792188e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001812358,"about_ca_topic_score_gemma":0.0002619317,"domain_scores_codex":[0.9993177,0.00002652551,0.0001219267,0.0002187966,0.00009117501,0.0002238955],"domain_scores_gemma":[0.9998083,0.00001920339,0.00001106518,0.000133107,0.000001746268,0.00002662667],"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":[0.00002227211,0.00001047983,0.05626165,0.000008275773,0.00001113287,0.000008530532,0.001883982,0.0001287895,0.9339212,0.00009939364,0.00031638,0.007327892],"study_design_scores_gemma":[0.0005475965,0.00006193175,0.1542544,0.000005769386,0.000006302471,0.000009610851,0.0001316928,0.0003948144,0.8074767,0.0006403573,0.03626718,0.0002036278],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965795,0.00002175655,0.000004231251,0.002166296,0.00007267086,0.0001011117,0.000001371129,0.0001694087,0.0008836563],"genre_scores_gemma":[0.990784,0.00007399213,0.0001362856,0.00008516066,0.00001168956,0.00001261153,0.00001956777,0.000006062832,0.008870644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1264445,"threshold_uncertainty_score":0.6455061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0195643208327422,"score_gpt":0.2612153853139499,"score_spread":0.2416510644812077,"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."}}