{"id":"W2488723297","doi":"10.1509/jppm.15.132","title":"The Squander Sequence: Understanding Food Waste at Each Stage of the Consumer Decision-Making Process","year":2016,"lang":"en","type":"article","venue":"Journal of Public Policy & Marketing","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":226,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Food waste; Transformative learning; Process (computing); Marketing; Sequence (biology); Consumption (sociology); Business; Consumer research; Waste management; Engineering; Psychology; Sociology; Computer science; Social science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004340321,0.0001238176,0.0001927593,0.00004122549,0.0007065773,0.000165143,0.00055847,0.00007275485,0.0001045917],"category_scores_gemma":[0.009647819,0.00002923112,0.0002214563,0.0006044382,0.0003284955,0.0003513217,0.000183951,0.0001850806,4.491101e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004953892,"about_ca_system_score_gemma":0.0002288758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007541978,"about_ca_topic_score_gemma":0.00007529786,"domain_scores_codex":[0.9977866,0.0004968126,0.0005921455,0.0001471624,0.0005852808,0.0003919932],"domain_scores_gemma":[0.9955694,0.002937272,0.0008109771,0.0001047637,0.0004594543,0.0001181266],"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":[0.0004798557,0.0001152112,0.1010647,0.00007841791,0.0001473141,0.000003479977,0.0003942639,0.0000200025,0.02187726,0.005415508,0.001120264,0.8692837],"study_design_scores_gemma":[0.003584766,0.001999323,0.261157,0.003431124,0.0001342858,0.001285743,0.5204546,0.0005254857,0.004558267,0.09771018,0.1035868,0.0015724],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980074,0.0002232334,0.00005237685,0.01852239,0.0001924478,0.0001221023,0.00001606914,0.000008566387,0.00078875],"genre_scores_gemma":[0.9991199,0.00007485627,0.00001233536,0.00007972305,0.0002880418,0.000001670109,1.255689e-7,0.00000170282,0.0004215935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8677113,"threshold_uncertainty_score":0.9986944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06740248567909532,"score_gpt":0.3120796798222874,"score_spread":0.2446771941431921,"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."}}