{"id":"W4406354049","doi":"10.1007/s10661-024-13583-1","title":"Identification of plant-based spilled oils using direct analysis in real-time–time-of-flight mass spectrometry with hydrophobic paper sampling","year":2025,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Environment and Climate Change Canada","keywords":"Environmental science; Petroleum; DART ion source; Oil spill; Mass spectrometry; Sediment; Sampling (signal processing); Microcosm; Petroleum product; Environmental chemistry; Pulp and paper industry; Chemistry; Chromatography; Environmental engineering; Geology; Computer science; Engineering","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":[0.0002689892,0.0001449995,0.000266458,0.0002444482,0.00008775185,0.00001945677,0.00007858362,0.00005285429,0.0002192628],"category_scores_gemma":[0.000003641523,0.0001356654,0.00006304371,0.0005499792,0.0001132503,0.0001325016,0.00004409748,0.00009231298,0.000005668614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004100701,"about_ca_system_score_gemma":0.00001109092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002484954,"about_ca_topic_score_gemma":0.00000568714,"domain_scores_codex":[0.9987799,0.00006833085,0.0003719676,0.0003272331,0.0002923546,0.0001602067],"domain_scores_gemma":[0.9994871,0.00005876109,0.0002024405,0.0002037126,0.000001939097,0.00004601849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001701129,0.00008292896,0.3092,0.00001152566,0.00005232475,9.841227e-7,0.00003266346,0.01131749,0.678744,0.000001186748,4.67704e-7,0.0005393558],"study_design_scores_gemma":[0.0003677843,0.00005282127,0.5581673,0.00005250689,0.0001423968,3.28627e-7,0.0001174948,0.009374995,0.4315995,0.000009558185,0.00001152859,0.0001037241],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970589,0.00003707529,0.001703053,0.00001445033,0.00006253743,0.0001609406,0.00001892224,0.00001528898,0.0009288003],"genre_scores_gemma":[0.9918128,0.00007615577,0.007887249,0.000003509227,0.00001240745,0.0000138678,0.00001832074,0.00000963618,0.000166027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2489673,"threshold_uncertainty_score":0.5532275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007490154464743782,"score_gpt":0.2547694805931804,"score_spread":0.2472793261284367,"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."}}