{"id":"W3196272632","doi":"10.1038/s41597-021-01002-w","title":"Inter-laboratory mass spectrometry dataset based on passive sampling of drinking water for non-target analysis","year":2021,"lang":"en","type":"article","venue":"Scientific Data","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Rijkswaterstaat; RECETOX Přírodovědecké Fakulty Masarykovy Univerzity; Masarykova Univerzita; Centre National de la Recherche Scientifique; Vlaamse Instelling voor Technologisch Onderzoek; Universitat de Girona; Örebro Universitet; Consiglio Nazionale delle Ricerche; Université Claude Bernard Lyon 1; Eidgenössische Anstalt für Wasserversorgung Abwasserreinigung und Gewässerschutz; Universität für Bodenkultur Wien; Bureau de Recherches Géologiques et Minières; National and Kapodistrian University of Athens; Euskal Herriko Unibertsitatea; Sveriges Lantbruksuniversitet; Aarhus Universitets Forskningsfond; University of Queensland; Vrije Universiteit Amsterdam; Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement; Norsk Institutt for Vannforskning; Jihočeská Univerzita v Českých Budějovicích; Universiteit van Amsterdam; Agence Nationale de la Recherche; Aarhus Universitet; Canadian Institute for Advanced Research; Ministry of Infrastructure and Water Management; Colorado State University","keywords":"Sampling (signal processing); Mass spectrometry; Environmental science; Passive sampling; Environmental chemistry; Chemistry; Computer science; Chromatography; Statistics; Mathematics; Calibration","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005438385,0.001059779,0.00133302,0.00304738,0.00111115,0.001284332,0.001897109,0.001286395,0.002829721],"category_scores_gemma":[0.007425385,0.0003524154,0.001059976,0.005245227,0.0008390793,0.0007044052,0.002254003,0.001068354,0.002587908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001466713,"about_ca_system_score_gemma":0.003618112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009277055,"about_ca_topic_score_gemma":0.01207806,"domain_scores_codex":[0.9925346,0.001389873,0.0006575721,0.002096193,0.002928682,0.0003930407],"domain_scores_gemma":[0.9906866,0.001470273,0.001345585,0.002457255,0.003694099,0.0003460699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.007540267,0.004049818,0.4455777,0.007554253,0.002835474,0.001906013,0.002101713,0.02566103,0.1828212,0.004282774,0.130008,0.1856617],"study_design_scores_gemma":[0.0003934156,0.001275323,0.5880317,0.0003329774,0.0006470745,0.00105462,0.001215267,0.01270904,0.09104493,0.004696758,0.2982886,0.000310436],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3399571,0.0008240725,0.0387535,0.0005177419,0.0002233245,0.001539413,0.6070067,0.002063413,0.009114704],"genre_scores_gemma":[0.212763,0.0003099436,0.04249473,0.0003313638,0.00007435914,0.002596611,0.7387385,0.000397182,0.002294195],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009277055,"threshold_uncertainty_score":0.02876127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0235785649677717,"score_gpt":0.2827320886429329,"score_spread":0.2591535236751611,"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."}}