{"id":"W1194978736","doi":"10.71781/12160","title":"Développement d’une méthode d’extraction des contaminants émergents dans les solides particulaires par LDTD-APCI-MS/MS","year":2013,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Contamination; Particulates; Extraction (chemistry); Chemistry; Environmental chemistry; Filtration (mathematics); Suspended solids; Chromatography; Detection limit; Sediment; Solid phase extraction; Environmental science; Wastewater; Environmental engineering; Geology","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":[0.002080759,0.001198895,0.0009860257,0.001379261,0.0007256679,0.001557087,0.0007746078,0.001648869,0.00174017],"category_scores_gemma":[0.001819604,0.0009238533,0.001277636,0.0008608966,0.001069846,0.001147875,0.0008607288,0.001918162,0.001850986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001062651,"about_ca_system_score_gemma":0.00273418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004525657,"about_ca_topic_score_gemma":0.006708615,"domain_scores_codex":[0.9973913,0.0002789554,0.0001514502,0.0007143287,0.001320733,0.000143105],"domain_scores_gemma":[0.99835,0.0004942855,0.0001788387,0.0001862749,0.0007351643,0.00005542152],"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":[0.00006186725,0.000043883,0.000943062,0.0003258619,0.00004124451,0.0001494106,0.00008127753,0.0004776597,0.9666852,0.0003222711,0.0001354724,0.03073267],"study_design_scores_gemma":[0.00002569475,0.0003839419,0.004760757,0.00005146751,0.00006786304,0.0006192066,0.0000525575,0.004805611,0.9678862,0.0002739342,0.02101885,0.00005387713],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2395605,0.009918685,0.7381078,0.0009391945,0.0004870649,0.001153708,0.001712142,0.002099887,0.006020945],"genre_scores_gemma":[0.1925466,0.006764362,0.7806094,0.0006783134,0.0001037559,0.0008427895,0.001681888,0.0002935742,0.01647933],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004525657,"threshold_uncertainty_score":0.01100421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02223659883510138,"score_gpt":0.2349820957454383,"score_spread":0.2127454969103369,"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."}}