{"id":"W4413120085","doi":"10.1016/j.biosystemseng.2025.104248","title":"Thermodynamic-based theoretical energy efficiency model for high-temperature grain drying","year":2025,"lang":"en","type":"article","venue":"Biosystems Engineering","topic":"Food Drying and Modeling","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lethbridge College; Agriculture and Agri-Food Canada; University of Lethbridge","funders":"Saskatchewan Wheat Development Commission; Alberta Innovates; Canada Foundation for Innovation; Agriculture Funding Consortium","keywords":"Grain drying; Thermodynamics; Process engineering; Environmental science; Energy (signal processing); Materials science; Engineering physics; Engineering; Physics; Composite material; Mathematics; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002385204,0.0001826469,0.0002013472,0.00003454528,0.0001638788,0.00007477804,0.0002176342,0.000161317,0.000004114537],"category_scores_gemma":[0.00006065983,0.00007984006,0.000113303,0.0002463394,0.00002016137,0.00003519788,0.00002942379,0.00009005617,7.850946e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004361932,"about_ca_system_score_gemma":0.00001702992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007684049,"about_ca_topic_score_gemma":0.00002922249,"domain_scores_codex":[0.9990168,0.0000203216,0.0002216002,0.0003047007,0.0001037123,0.0003328207],"domain_scores_gemma":[0.9996078,0.0001637814,0.00003150073,0.00008000604,0.00005691475,0.0000599813],"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":[0.00001400437,0.00002198758,0.000006679842,0.00005271928,0.00001161095,4.572783e-7,0.00001905405,0.05554569,0.7641469,0.1785471,0.00004503117,0.001588748],"study_design_scores_gemma":[0.0001734856,0.00004508367,0.00004100527,0.0001749163,0.00001152455,6.901364e-7,0.00002194508,0.9758254,0.02276032,0.0004719721,0.0002836858,0.0001899182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.953097,0.0003159711,0.04499393,0.0004282763,0.0004989276,0.0002150819,0.00004832644,0.0002967839,0.0001057046],"genre_scores_gemma":[0.9988249,0.000003288375,0.0006157181,0.0001223818,0.0001490561,0.00007440411,0.00004640465,0.000003137421,0.000160699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9202797,"threshold_uncertainty_score":0.3255783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006143240971495027,"score_gpt":0.1859599134100044,"score_spread":0.1798166724385094,"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."}}