{"id":"W1818928769","doi":"10.1039/c5ja00203f","title":"Optimization of the double spike technique using peak jump collection by a Monte Carlo method: an example for the determination of Ca isotope ratios","year":2015,"lang":"en","type":"article","venue":"Journal of Analytical Atomic Spectrometry","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"National Natural Science Foundation of China","keywords":"Jump; Monte Carlo method; Spike (software development); Isotope; Chemistry; Statistics; Mathematics; Analytical Chemistry (journal); Computer science; Chromatography; Physics; Nuclear physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001358685,0.0008965484,0.001023013,0.0007161594,0.0004729658,0.000788637,0.001107518,0.001011821,0.0008841273],"category_scores_gemma":[0.001605399,0.00044766,0.0006361054,0.0009524245,0.0004270803,0.0005084678,0.0005576555,0.00100964,0.0004405624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004758899,"about_ca_system_score_gemma":0.001178238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001843104,"about_ca_topic_score_gemma":0.002619757,"domain_scores_codex":[0.9991056,0.0001547356,0.00003539339,0.0001746445,0.0004738228,0.00005579047],"domain_scores_gemma":[0.9992943,0.000290173,0.0000606605,0.0001221627,0.0002092667,0.00002336765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004789795,0.0003503684,0.002243095,0.0003933551,0.0001499213,0.0003182614,0.0001551766,0.04858452,0.6847134,0.01181253,0.001651055,0.2491495],"study_design_scores_gemma":[0.00004829384,0.0002964477,0.001835523,0.00001626741,0.00007061059,0.0004750285,0.00002399263,0.5758708,0.4110589,0.003910854,0.006283579,0.0001097059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02141297,0.0002868988,0.9757724,0.0001048168,0.00004070573,0.00007502447,0.00006268057,0.001269619,0.0009749077],"genre_scores_gemma":[0.1334291,0.0002396761,0.8647504,0.00005603832,0.00001410041,0.00008914289,0.00009010091,0.0002220173,0.001109473],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001843104,"threshold_uncertainty_score":0.007185519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03996321196985572,"score_gpt":0.3219773815403956,"score_spread":0.2820141695705399,"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."}}