{"id":"W4391651947","doi":"10.1017/rdc.2023.116","title":"ADVANCING ANTARCTIC SEDIMENT CHRONOLOGY THROUGH COMBINED RAMPED PYROLYSIS OXIDATION AND PYROLYSIS-GC-MS","year":2024,"lang":"en","type":"article","venue":"Radiocarbon","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Ministerio de Ciencia e Innovación; Ministry of Science and Innovation, New Zealand; Ministry of Oceans and Fisheries; Ministry of Business, Innovation and Employment; Korea Polar Research Institute; European Commission","keywords":"Chronology; Radiocarbon dating; Pyrolysis; Sediment; Geology; Accelerator mass spectrometry; Environmental chemistry; Gas chromatography–mass spectrometry; Mass spectrometry; Mineralogy; Oceanography; Geochemistry; Paleontology; Chemistry; Chromatography; Organic chemistry","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":[0.0006063374,0.0006579377,0.0002952976,0.001830257,0.0003992666,0.0009487686,0.0003657466,0.0002804446,0.0009308268],"category_scores_gemma":[0.0005107662,0.0003174991,0.0004654171,0.001354413,0.0002342642,0.0004353898,0.0005544847,0.0003159356,0.0005032751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003031265,"about_ca_system_score_gemma":0.0005107272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004311066,"about_ca_topic_score_gemma":0.01223179,"domain_scores_codex":[0.9996718,0.00003648912,0.00002143567,0.0001043042,0.0001410334,0.00002493965],"domain_scores_gemma":[0.9996598,0.00005137177,0.00006303025,0.00004705595,0.0001602135,0.00001863698],"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":[0.0003540497,0.00005065237,0.0695207,0.0002640813,0.0002166714,0.0004406138,0.0001930918,0.005141356,0.8402725,0.000305627,0.0004713847,0.08276915],"study_design_scores_gemma":[0.00003087385,0.0003575656,0.215442,0.00009046083,0.0002874634,0.0008135522,0.000348322,0.03321797,0.7324241,0.00046876,0.01639523,0.0001236453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9310597,0.001488717,0.05604769,0.00007867601,0.00007782054,0.0002354926,0.004562932,0.0009151098,0.005534047],"genre_scores_gemma":[0.8336188,0.001692278,0.1596029,0.000078293,0.0000397005,0.0001206728,0.001796877,0.0001829172,0.002867598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004311066,"threshold_uncertainty_score":0.008571923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006726582880697492,"score_gpt":0.223987182485083,"score_spread":0.2172605996043855,"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."}}