{"id":"W3085908747","doi":"10.1016/j.chemosphere.2020.128325","title":"Calibration of organic-diffusive gradients in thin films (o-DGT) passive samplers for perfluorinated alkyl acids in water","year":2020,"lang":"en","type":"article","venue":"Chemosphere","topic":"Per- and polyfluoroalkyl substances research","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Winnipeg; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canada Research Chairs","keywords":"Diffusive gradients in thin films; Polyacrylamide; Chemistry; Wax; Alkyl; Environmental chemistry; Agarose; Diffusion; Passive sampling; Calibration; Analytical Chemistry (journal); Chromatography; Organic chemistry; Metal; Polymer chemistry; Thermodynamics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008597489,0.0005945408,0.0002239162,0.0004167393,0.0003495772,0.0005799209,0.0005394768,0.0006628569,0.0004903308],"category_scores_gemma":[0.001597547,0.0004245286,0.0002381277,0.0002504476,0.0003235886,0.0004282562,0.0003998507,0.0004708408,0.0003676823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005228611,"about_ca_system_score_gemma":0.0004486906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00245089,"about_ca_topic_score_gemma":0.004170613,"domain_scores_codex":[0.9992556,0.0001568076,0.00003967711,0.0002173777,0.000275903,0.00005459127],"domain_scores_gemma":[0.9993733,0.0003082798,0.0000844723,0.00005674372,0.0001454039,0.00003181823],"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":[0.000123239,0.00002551649,0.002637359,0.00003205311,0.00001305542,0.00001103321,0.00003864168,0.0002713113,0.9918108,0.00006368791,0.00004963077,0.004923769],"study_design_scores_gemma":[0.00001199057,0.0001510228,0.003805445,0.000005452729,0.00001540788,0.00005477776,0.00002787199,0.003526103,0.9915143,0.00005147234,0.0008295404,0.000006637018],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9172476,0.001011078,0.07863069,0.0001411461,0.0001515522,0.0002034634,0.0005086096,0.0003667625,0.001739002],"genre_scores_gemma":[0.9459769,0.001198768,0.05000756,0.0002621895,0.00003664746,0.0001549647,0.0004490448,0.00006053465,0.00185345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00245089,"threshold_uncertainty_score":0.004873216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0188193060373852,"score_gpt":0.244261269853326,"score_spread":0.2254419638159408,"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."}}