{"id":"W4413571173","doi":"10.64628/aam.3mrrjecyg","title":"Reduce your food waste to save money, boost health and reduce CO2 emissions","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Food waste; Business; Natural resource economics; Waste management; Food security; Greenhouse gas; Environmental economics; Environmental science; Economics; Agriculture; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002013383,0.0004554014,0.0003730477,0.0004936462,0.0003774618,0.001144159,0.0002404051,0.001158697,0.02833464],"category_scores_gemma":[0.0009171518,0.000140403,0.0004046506,0.0005634293,0.0004612364,0.001288919,0.0005411338,0.0005999814,0.004986855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004722042,"about_ca_system_score_gemma":0.0003292968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001272868,"about_ca_topic_score_gemma":0.0009453754,"domain_scores_codex":[0.9998379,0.00001562949,0.000003449964,0.00003251754,0.00008608148,0.0000243974],"domain_scores_gemma":[0.9998393,0.00003840215,0.00001361557,0.00003949128,0.00004668701,0.00002247128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001867619,0.0002583536,0.001552094,0.0005491062,0.0001194205,0.0004118962,0.0003001702,0.007337142,0.04533667,0.5558543,0.113094,0.2750002],"study_design_scores_gemma":[0.00005187199,0.00007620362,0.004063143,0.00009450856,0.00004988727,0.00103608,0.0002965485,0.03042697,0.05502569,0.7219365,0.1869017,0.00004074648],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.1848518,0.007808208,0.2106077,0.04012495,0.006986158,0.0000918183,0.002275146,0.002403276,0.5448508],"genre_scores_gemma":[0.6840367,0.00391848,0.0508827,0.001371715,0.001046887,0.00005855073,0.0006566028,0.0008062915,0.257222],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.02833464,"threshold_uncertainty_score":0.09478885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05450929500497093,"score_gpt":0.2979161061410148,"score_spread":0.2434068111360438,"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."}}