{"id":"W3201120732","doi":"10.1016/j.wasman.2021.08.039","title":"Directly observing household food waste generation using composition audits in a Canadian municipality","year":2021,"lang":"en","type":"article","venue":"Waste Management","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"University of Guelph","keywords":"Audit; Food waste; Per capita; Business; Household waste; Agricultural economics; Food preparation; Municipal solid waste; Agricultural science; Food processing; Environmental health; Environmental science; Waste management; Engineering; Economics; Food science; Medicine; Population; Accounting","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003329185,0.0001264601,0.0001444529,0.00003821832,0.0002401256,0.0001086727,0.0001309355,0.00005978745,0.00004702729],"category_scores_gemma":[0.00001289466,0.00007174741,0.00006568949,0.0005850596,0.00002132711,0.0001346853,0.0001202516,0.00009097181,0.000001591606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004529426,"about_ca_system_score_gemma":0.00002845906,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05689728,"about_ca_topic_score_gemma":0.4681845,"domain_scores_codex":[0.9986264,0.0001983324,0.000244832,0.0003563133,0.0001834485,0.0003906962],"domain_scores_gemma":[0.9995993,0.00001467116,0.00005162859,0.0001200132,0.0000627295,0.0001517043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007705102,0.001097653,0.01821735,0.0004403825,0.0002547282,0.0004616539,0.00140168,0.1058189,0.3660868,0.01343644,0.001333826,0.4913736],"study_design_scores_gemma":[0.003093928,0.001014296,0.2192108,0.0007909471,0.0003041716,0.00009381561,0.3403395,0.2720039,0.105535,0.001754054,0.0522996,0.003559983],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961348,0.0001437813,0.000006765952,0.001086059,0.0002492516,0.0002820141,0.00002391042,0.00003176805,0.002041652],"genre_scores_gemma":[0.9989777,0.00002812488,0.0002457876,0.0002479624,0.0001842198,0.00001625863,0.000102682,0.000001519949,0.0001957168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4878136,"threshold_uncertainty_score":0.9493829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07466950282612428,"score_gpt":0.2404625321057064,"score_spread":0.1657930292795821,"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."}}