{"id":"W2581540037","doi":"10.3390/bioengineering4010007","title":"HHV Predicting Correlations for Torrefied Biomass Using Proximate and Ultimate Analyses","year":2017,"lang":"en","type":"article","venue":"Bioengineering","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":161,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Biomass (ecology); Proximate; Torrefaction; Environmental science; Pulp and paper industry; Waste management; Process engineering; Chemistry; Engineering; Food science; Biology; Agronomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000786426,0.0001873653,0.0001859083,0.0001012776,0.0002824925,0.0001616436,0.0001921922,0.00009657327,0.00000825406],"category_scores_gemma":[0.0001537979,0.0001910721,0.00005194499,0.0000691337,0.0000453721,0.0003273562,0.00007065692,0.00007255992,0.00000291312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004904613,"about_ca_system_score_gemma":0.000008758159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001323586,"about_ca_topic_score_gemma":0.000001190156,"domain_scores_codex":[0.9992291,0.000002662064,0.0002029171,0.0001953727,0.00008602664,0.0002838681],"domain_scores_gemma":[0.9994534,0.00006091109,0.00006465896,0.0002753409,0.00004599095,0.00009967636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000636446,0.000005046084,0.002316279,0.0004050349,0.00007402938,0.000001753121,0.00006478091,0.005812885,0.9902918,0.0000536889,0.0000315724,0.0009367697],"study_design_scores_gemma":[0.0002949792,0.000008551118,0.001176113,0.0000834773,0.00004862026,0.000006885808,0.00003002021,0.5751972,0.4227724,0.0000307645,0.0001466054,0.0002043758],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9290807,0.0005447409,0.06884979,0.00003132319,0.0004787814,0.0002369633,0.00004743044,0.0005892211,0.0001410913],"genre_scores_gemma":[0.9885077,0.00002058515,0.01126837,0.000003135366,0.00009697529,0.00002561848,0.00001017535,0.00004880087,0.00001860252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5693843,"threshold_uncertainty_score":0.7791696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05570295604256657,"score_gpt":0.3072065254955663,"score_spread":0.2515035694529997,"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."}}