{"id":"W2461125375","doi":"10.1016/j.lithos.2016.06.020","title":"Carbon and nitrogen isotope systematics in diamond: Different sensitivities to isotopic fractionation or a decoupled origin?","year":2016,"lang":"en","type":"article","venue":"Lithos","topic":"Geological and Geochemical Analysis","field":"Earth and Planetary Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Diamond; δ13C; Isotopes of nitrogen; Geology; Nitrogen; Isotopes of carbon; Cathodoluminescence; Kimberlite; Isotope; Analytical Chemistry (journal); Microbeam; Fractionation; Mantle (geology); Isotope fractionation; Carbon fibers; Mineralogy; Stable isotope ratio; Geochemistry; Materials science; Chemistry; Environmental chemistry; Luminescence; Physics","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":[0.0006884093,0.0003163748,0.0003748144,0.000826397,0.0003354035,0.000706874,0.0005199778,0.0004948732,0.001666366],"category_scores_gemma":[0.001159248,0.0003002471,0.0003421856,0.000672842,0.0009245392,0.0007837146,0.0007045466,0.0003662359,0.0002446453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004578328,"about_ca_system_score_gemma":0.0003579132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004867224,"about_ca_topic_score_gemma":0.009951436,"domain_scores_codex":[0.9996909,0.00004954348,0.00001852546,0.0001205854,0.00006407527,0.0000563692],"domain_scores_gemma":[0.9996506,0.0001118488,0.00007036861,0.00006676658,0.00007282432,0.00002759474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001252184,0.00009031651,0.5573657,0.0002413384,0.0006310514,0.0002891959,0.001104663,0.000767358,0.384349,0.007471607,0.0003079854,0.04612963],"study_design_scores_gemma":[0.00006625865,0.0001260104,0.9545953,0.0000349398,0.0001931353,0.0003627551,0.0008853611,0.001760337,0.03587443,0.00391701,0.002148203,0.0000362858],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959427,0.0005500835,0.001262203,0.0001535741,0.00001260228,0.000004261019,0.0001730759,0.00001973359,0.001881835],"genre_scores_gemma":[0.9985034,0.0002225205,0.0005748993,0.00009495157,0.000007411034,0.000003280144,0.000143059,0.00001772676,0.0004326695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004867224,"threshold_uncertainty_score":0.009677768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01481169921222231,"score_gpt":0.2139661405221679,"score_spread":0.1991544413099456,"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."}}