{"id":"W2105336999","doi":"10.5539/ibr.v3n3p111","title":"Energy Use in Agriculture Sector: Input-Output Analysis","year":2010,"lang":"en","type":"article","venue":"International Business Research","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Tenaga Nasional; Tenaga Nasional Berhad","keywords":"Social connectedness; Agriculture; Electricity; Economic sector; Coal; Energy sector; Business; Natural resource economics; Input–output model; Energy (signal processing); Fossil fuel; Economics; Agricultural economics; Economy; Macroeconomics; Mathematics; Engineering; Statistics; Geography; Waste management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005761983,0.0001145333,0.0001281404,0.000322863,0.00009220895,0.0001524104,0.0005279753,0.0001147912,0.006519813],"category_scores_gemma":[0.0003823745,0.0000918269,0.00006939127,0.001973296,0.0003288965,0.0006196008,0.0005067097,0.0004415961,0.0001713837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000477249,"about_ca_system_score_gemma":0.00001893185,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01783758,"about_ca_topic_score_gemma":0.02391312,"domain_scores_codex":[0.997942,0.0001029668,0.0002011566,0.0003703341,0.0010203,0.0003632971],"domain_scores_gemma":[0.9993291,0.0001409207,0.00003333577,0.0002996174,0.00008159457,0.0001154148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000283465,0.0002280761,0.9768011,0.000001978784,0.00003628662,0.00003478217,0.0001089624,0.001721974,0.0175104,0.0001582941,0.001504875,0.001864903],"study_design_scores_gemma":[0.0001577589,0.000007786856,0.959163,0.000002100078,0.000005899756,0.000003726165,0.00006011216,0.0007878096,0.0009032577,0.0005557931,0.03824633,0.0001064774],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855365,0.000004936233,0.0002576398,0.0009595201,0.0001647895,0.00009080805,0.00001407283,0.00001552919,0.01295625],"genre_scores_gemma":[0.9918777,0.00001898693,0.0002253021,0.00009611814,0.00008564039,0.00002969781,0.00006346234,0.000008674839,0.007594359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03674145,"threshold_uncertainty_score":0.9943883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03113454899739442,"score_gpt":0.3197592676033022,"score_spread":0.2886247186059078,"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."}}