{"id":"W3098284269","doi":"10.1029/2020jd033125","title":"Seasonal Cycle of Isotope‐Based Source Apportionment of Elemental Carbon in Airborne Particulate Matter and Snow at Alert, Canada","year":2020,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Stockholms Universitet; Environment and Climate Change Canada","keywords":"Snow; Environmental science; Particulates; Aerosol; Arctic; Isotopes of carbon; Atmospheric sciences; Environmental chemistry; Carbon fibers; Combustion; Biomass (ecology); Radiocarbon dating; Atmosphere (unit); Carbon cycle; Total organic carbon; Chemistry; Meteorology; Oceanography; Geology; Ecology; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001703777,0.0003305073,0.0002633076,0.001281281,0.001187471,0.00072069,0.000536072,0.0002061117,0.001093856],"category_scores_gemma":[0.0003655029,0.0001840848,0.0002487245,0.001435409,0.0003593604,0.0002058401,0.0005168932,0.0002472463,0.0001514587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01040875,"about_ca_system_score_gemma":0.008855057,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.978028,"about_ca_topic_score_gemma":0.9903238,"domain_scores_codex":[0.9997901,0.000006717071,0.00000646753,0.00004076587,0.00009154258,0.00006446036],"domain_scores_gemma":[0.9992211,0.00002180734,0.00005138984,0.00001220659,0.0005739597,0.0001196478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002336342,0.0000237745,0.9774423,0.00003810483,0.00009313725,0.0001249176,0.0007578889,0.0005811887,0.008666019,0.0001384469,0.002184132,0.009716441],"study_design_scores_gemma":[0.000001891558,0.000006115401,0.9977487,0.000005784426,0.000008501891,0.00001733656,0.0002909303,0.0004350533,0.0005566092,0.00001251765,0.0009109989,0.000005642692],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927756,0.0002233781,0.0001842601,0.00007448802,0.000009947613,0.00001418293,0.00408874,0.00003118893,0.002598317],"genre_scores_gemma":[0.9952404,0.0001380398,0.0002233008,0.00004228795,0.000003481978,0.000008076001,0.002795588,0.000009154284,0.001539742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.021972,"threshold_uncertainty_score":0.07552105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01793556984931392,"score_gpt":0.2454340259350497,"score_spread":0.2274984560857358,"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."}}