{"id":"W4406994677","doi":"10.3390/thermo5010003","title":"Energy and Exergy Analyses Applied to a Crop Plant System","year":2025,"lang":"en","type":"article","venue":"Thermo","topic":"Sustainability and Ecological Systems Analysis","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Agricultural Adaptation Council","keywords":"Exergy; Crop; Environmental science; Energy crop; Agricultural engineering; Energy (signal processing); Agronomy; Agroforestry; Bioenergy; Biology; Process engineering; Engineering; Mathematics; Biotechnology; Biofuel; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001627051,0.0003899331,0.0003861276,0.0006420708,0.0002954556,0.0004379464,0.0001998333,0.0002297925,0.00151295],"category_scores_gemma":[0.0004059054,0.000127014,0.0005617935,0.0006849673,0.0002992361,0.0003586978,0.0003321052,0.0003147955,0.0001693983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003395973,"about_ca_system_score_gemma":0.0003372152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003107662,"about_ca_topic_score_gemma":0.002274227,"domain_scores_codex":[0.999933,0.00001801333,0.000005558582,0.000013457,0.00002090164,0.000009065273],"domain_scores_gemma":[0.9998955,0.00006866238,0.00001049033,0.000007556251,0.0000148908,0.000002949587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001250119,0.00008098361,0.0110587,0.0003166723,0.0001255394,0.0004787721,0.0002247291,0.8044273,0.1228587,0.01670193,0.0002353652,0.04336632],"study_design_scores_gemma":[0.000006574469,0.00009996747,0.01234673,0.00001162368,0.00002933318,0.00009421755,0.0001008559,0.9597145,0.01872253,0.006946451,0.00190833,0.000018907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.705567,0.0007144277,0.2795357,0.00007619937,0.00002838908,0.0001336846,0.0005988254,0.0002188739,0.01312683],"genre_scores_gemma":[0.9832051,0.0002973303,0.01460787,0.000006563297,0.000007033484,0.00007195888,0.0001390657,0.00002543593,0.001639649],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003107662,"threshold_uncertainty_score":0.006179154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246581767068162,"score_gpt":0.2393293884877398,"score_spread":0.2268635708170582,"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."}}