{"id":"W4417153422","doi":"10.1039/d5en00095e","title":"Exploring environmental nanobiogeochemistry using field-flow fractionation and ICP-MS-based tools: background and fundamentals","year":2025,"lang":"en","type":"article","venue":"Environmental Science Nano","topic":"Field-Flow Fractionation Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; GDG Environnement; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Natural (archaeology); Field (mathematics); Environmental systems; Perspective (graphical); Nanoparticle; Instrumentation (computer programming); Particle (ecology)","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":[0.001264603,0.0009435514,0.0008351631,0.002109182,0.0005088077,0.001888366,0.001012048,0.001552394,0.001738711],"category_scores_gemma":[0.0007714174,0.000562263,0.0005466372,0.001491187,0.001304035,0.002374193,0.0009699789,0.002148373,0.001136152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001065061,"about_ca_system_score_gemma":0.001206981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001535738,"about_ca_topic_score_gemma":0.001562895,"domain_scores_codex":[0.9993984,0.0001138186,0.00003934184,0.0001609458,0.0002383391,0.000049139],"domain_scores_gemma":[0.9995776,0.0002400172,0.0000437417,0.00002054499,0.00009557957,0.00002251189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001359043,0.0003489378,0.002395754,0.02017245,0.0001721857,0.0009515274,0.001287832,0.005673121,0.3068295,0.1136225,0.01583318,0.5325772],"study_design_scores_gemma":[0.00001800692,0.0004488639,0.003398555,0.002393856,0.00009600188,0.002950794,0.0007383841,0.005471406,0.1654757,0.05674218,0.7620959,0.0001702375],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.01581377,0.6163261,0.3368292,0.004235179,0.001053951,0.0003042946,0.0007433888,0.0005127728,0.02418128],"genre_scores_gemma":[0.06058463,0.6847767,0.2417206,0.002102441,0.001513875,0.000431994,0.0009431837,0.0001380053,0.007788597],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002109182,"threshold_uncertainty_score":0.007727563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04049938816878313,"score_gpt":0.2495946802745721,"score_spread":0.209095292105789,"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."}}