{"id":"W2753855920","doi":"10.1021/acs.energyfuels.7b01863","title":"X-ray Photoelectron Spectroscopy Analysis of Hydrotreated Athabasca Asphaltenes","year":2017,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"China National Offshore Oil Corporation; Natural Sciences and Engineering Research Council of Canada; Kungl. Vetenskaps- och Vitterhets-Samhället i Göteborg","keywords":"Asphaltene; Hydrodesulfurization; X-ray photoelectron spectroscopy; Hydrodeoxygenation; Catalysis; Oil sands; Sulfur; Chemistry; Oxygen; Reactivity (psychology); Nitrogen; Chemical engineering; Analytical Chemistry (journal); Asphalt; Materials science; Organic chemistry; Selectivity; Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000120865,0.000248343,0.0006600341,0.0002601968,0.0003657425,0.0001253661,0.0006577499,0.0001354668,0.001447538],"category_scores_gemma":[0.00006842013,0.0002250438,0.0004991056,0.0003864709,0.0001314832,0.0001643055,0.00007504337,0.0001245828,0.000008261203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006005012,"about_ca_system_score_gemma":0.00006406679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00270545,"about_ca_topic_score_gemma":0.000527133,"domain_scores_codex":[0.9984537,0.00002105252,0.0003522636,0.0004532243,0.0003208468,0.0003989144],"domain_scores_gemma":[0.9981334,0.00003939382,0.0005165,0.001099591,0.0000947226,0.0001163769],"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":[0.00003729302,0.000103891,0.0131875,0.00002881703,0.002284073,0.00001360642,0.00003983639,0.0001500835,0.9790789,0.0001177413,0.0000462545,0.004911957],"study_design_scores_gemma":[0.0003236762,0.00002665438,0.002435028,0.00003920867,0.002059094,0.000001016969,0.00002175448,0.001848485,0.9893137,0.0001097616,0.003590074,0.0002315635],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9102199,0.0008262049,0.0004083737,0.00007848437,0.00002716149,0.000002645435,0.00002813843,0.00008215478,0.08832695],"genre_scores_gemma":[0.9760035,0.0002372104,0.0002562226,0.00003143548,0.0001214421,0.00001402358,0.0001017035,0.00002664266,0.02320782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06578361,"threshold_uncertainty_score":0.9994653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00996593058584534,"score_gpt":0.2544158883019251,"score_spread":0.2444499577160798,"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."}}