{"id":"W4412160378","doi":"10.1021/acs.energyfuels.5c01309","title":"Interlaboratory Study of Sample Homogeneity Impact on CHNS, Water, and ICP Analysis of Biomass Liquefaction Oils","year":2025,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Canadian Forest Service; Pacific Northwest National Laboratory; Office of Energy Research and Development; Natural Resources Canada; U.S. Forest Service; Innotech Alberta","keywords":"Liquefaction; Homogeneity (statistics); Environmental science; Environmental chemistry; Chemistry; Pulp and paper industry; Organic chemistry; Mathematics; Statistics; Engineering","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05470193,0.001790966,0.0009746152,0.001906209,0.002710751,0.002383056,0.001486191,0.001883192,0.002390636],"category_scores_gemma":[0.06050754,0.001074103,0.00131774,0.002240685,0.003391751,0.0006509859,0.002981819,0.001141216,0.001109286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468406,"about_ca_system_score_gemma":0.002767334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004809524,"about_ca_topic_score_gemma":0.008870613,"domain_scores_codex":[0.9173096,0.03335513,0.007795735,0.01729064,0.02244031,0.001808714],"domain_scores_gemma":[0.9377658,0.02437036,0.004816384,0.01530075,0.01691276,0.000833866],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005141187,0.002136761,0.1081227,0.001090616,0.001849338,0.0004329679,0.006113165,0.003494049,0.8089049,0.002287807,0.002661823,0.05776455],"study_design_scores_gemma":[0.0003520381,0.009035611,0.1743411,0.000209117,0.001950343,0.001021175,0.001386822,0.007003953,0.7768468,0.001687545,0.02595292,0.000212683],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7183246,0.002652562,0.2537397,0.0007220401,0.001226392,0.007176076,0.002534978,0.001857974,0.01176575],"genre_scores_gemma":[0.8371999,0.0003883004,0.1444189,0.001024365,0.0002211773,0.006384807,0.003656326,0.0008816016,0.005824665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9452981,"threshold_uncertainty_score":0.2892949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007135175233668431,"score_gpt":0.2399780910610497,"score_spread":0.2328429158273813,"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."}}