{"id":"W4409642467","doi":"10.1109/emergin63207.2024.10961253","title":"Enhancing Retail Sustainability: Data-Driven Approach for Food Waste Detection and Prevention","year":2024,"lang":"en","type":"article","venue":"","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Sustainability; Food waste; Business; Computer science; Environmental economics; Waste management; Engineering; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005564757,0.0001029742,0.0001175912,0.00001578324,0.0001867392,0.000158051,0.0001236015,0.00008195915,0.00002742478],"category_scores_gemma":[0.000159966,0.00004041865,0.00006415907,0.0002492147,0.00005209933,0.0003634334,0.0001168498,0.00008477151,4.411691e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008016833,"about_ca_system_score_gemma":0.00002510008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003737075,"about_ca_topic_score_gemma":0.0005495105,"domain_scores_codex":[0.998908,0.00007081874,0.0001869416,0.0005253115,0.000103982,0.0002049014],"domain_scores_gemma":[0.99959,0.0001032593,0.00002429425,0.0001034663,0.0001137272,0.00006518921],"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":[0.00003670307,0.00005166424,0.00004532541,0.0003571646,0.00002617629,2.76932e-7,0.00009333718,0.00002557574,0.01661251,0.001013377,0.00007667626,0.9816612],"study_design_scores_gemma":[0.0007670745,0.006900494,0.004086809,0.00009523301,0.0002749163,0.0001052184,0.4294312,0.3768054,0.03941966,0.05482006,0.08591389,0.001379995],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811983,0.0003283272,0.01575918,0.001126404,0.0001301207,0.0008787449,0.00003459036,0.0001958385,0.0003484602],"genre_scores_gemma":[0.9972097,0.00001441483,0.0008686102,0.00001500216,0.0002294805,0.00006714302,0.0001023671,0.000001120104,0.001492137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9802812,"threshold_uncertainty_score":0.1648225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04123673075610513,"score_gpt":0.2661301239422826,"score_spread":0.2248933931861775,"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."}}