{"id":"W2891320433","doi":"10.1016/j.esd.2018.08.006","title":"Energy use and fossil CO2 emissions for the Canadian fruit and vegetable industries","year":2018,"lang":"en","type":"article","venue":"Energy Sustainable Development/Energy for sustainable development","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada","keywords":"Irrigation; Fossil fuel; Environmental science; Energy supply; Fertilizer; Agricultural science; Agricultural economics; Agricultural engineering; Agronomy; Energy (signal processing); Engineering; Waste management; Mathematics; Economics; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0003437918,0.0003619423,0.0001379474,0.001536432,0.001361324,0.001129018,0.0007797743,0.0004034908,0.004452715],"category_scores_gemma":[0.000754807,0.0001611695,0.000686441,0.003690312,0.0003486812,0.0005482537,0.0004634172,0.0004125816,0.0002912695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04575317,"about_ca_system_score_gemma":0.03218965,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9981279,"about_ca_topic_score_gemma":0.9994205,"domain_scores_codex":[0.9996064,0.00001697376,0.00001010709,0.00003344298,0.000176711,0.0001563487],"domain_scores_gemma":[0.9995269,0.00003935286,0.00004206922,0.000009329759,0.0003017497,0.00008071581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008294047,0.0002169526,0.8741288,0.000447579,0.0003701332,0.0005833131,0.001590829,0.01023343,0.00402071,0.008759721,0.02555447,0.07326486],"study_design_scores_gemma":[0.000008137567,0.00001745129,0.974676,0.00005548844,0.00007928193,0.00003953738,0.00238277,0.002095815,0.001054088,0.0003286235,0.01923526,0.0000277176],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9484718,0.004528305,0.0003048214,0.001589988,0.00002948811,0.00003080694,0.02264302,0.00002860591,0.02237303],"genre_scores_gemma":[0.9782774,0.002220229,0.0002244261,0.0001185793,0.000005306755,0.000008888982,0.00652785,0.00001160522,0.01260554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04575317,"threshold_uncertainty_score":0.331964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01100097096641007,"score_gpt":0.2028552206623726,"score_spread":0.1918542496959626,"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."}}