{"id":"W3081757089","doi":"10.3390/agronomy10091309","title":"Optimising Sample Preparation and Calibrations in EDXRF for Quantitative Soil Analysis","year":2020,"lang":"en","type":"article","venue":"Agronomy","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Teagasc; Queen's University Belfast","keywords":"Soil test; Soil water; Sample preparation; Calibration; Soil texture; Inductively coupled plasma; Wax; Pellet; Extraction (chemistry); Inductively coupled plasma atomic emission spectroscopy; Inductively coupled plasma mass spectrometry; Chemistry; Analytical Chemistry (journal); Environmental science; Mass spectrometry; Environmental chemistry; Materials science; Chromatography; Soil science; Mathematics; Plasma","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":[0.006346985,0.001264573,0.0008555517,0.001414133,0.0006586802,0.0006755582,0.001067753,0.001009181,0.002251421],"category_scores_gemma":[0.00605279,0.0007712755,0.0005947315,0.001181809,0.0007065847,0.0008529603,0.0007691954,0.0006952895,0.001281194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004448288,"about_ca_system_score_gemma":0.0007140114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008052775,"about_ca_topic_score_gemma":0.002592324,"domain_scores_codex":[0.9954225,0.001118107,0.0003814618,0.001003734,0.00187659,0.0001976012],"domain_scores_gemma":[0.9979663,0.0006732376,0.0002035775,0.0003087561,0.0008114421,0.00003677409],"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":[0.000150621,0.0001133722,0.001335494,0.0003118657,0.00002864026,0.0000741457,0.0001298101,0.0007985338,0.9739646,0.0002506244,0.0002843613,0.02255788],"study_design_scores_gemma":[0.00003868619,0.0004361866,0.004607436,0.00005500851,0.00005646249,0.0003228528,0.0001207793,0.005732346,0.9754506,0.0003857025,0.01275318,0.00004073805],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1493423,0.001225877,0.8426008,0.0001918682,0.0001332632,0.001770494,0.0008842889,0.001967891,0.001883262],"genre_scores_gemma":[0.1077247,0.001329377,0.8842562,0.0001762732,0.00003152909,0.002796001,0.001247236,0.0004793303,0.001959382],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006346985,"threshold_uncertainty_score":0.03356647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03856557077798353,"score_gpt":0.2772429791516234,"score_spread":0.2386774083736399,"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."}}