{"id":"W2120522924","doi":"10.1504/ijex.2011.043921","title":"Simple price-driven Reverse Logistics system with entropy and exergy costs","year":2011,"lang":"en","type":"article","venue":"International Journal of Exergy","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; Toronto Metropolitan University","funders":"","keywords":"Exergy; Economic order quantity; Computer science; Entropy (arrow of time); Profit (economics); Mathematical optimization; Operations research; Economics; Thermodynamics; Microeconomics; Mathematics; Supply chain; Physics","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":[0.0002750101,0.0001595252,0.000213129,0.0004544113,0.00006146976,0.0001929939,0.0004844264,0.00004112362,0.0002518093],"category_scores_gemma":[0.0001174789,0.0001282518,0.00006102556,0.0001619383,0.00006706863,0.0008076293,0.0002334066,0.0001226816,0.00002627383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002538012,"about_ca_system_score_gemma":0.00003686134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007251056,"about_ca_topic_score_gemma":0.00005571403,"domain_scores_codex":[0.9986466,0.00001440244,0.0004046413,0.0001607114,0.0005575715,0.0002161278],"domain_scores_gemma":[0.9981257,0.00004130324,0.0006698717,0.0001332664,0.0009995934,0.00003026578],"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":[0.002136782,0.0004849535,0.08285446,0.000455332,0.001380726,0.007234265,0.0005046409,0.003801546,0.0002851018,0.8592764,0.03295095,0.008634876],"study_design_scores_gemma":[0.01042304,0.0004949702,0.05248804,0.001458432,0.0006656043,0.0009533277,0.02526589,0.03079513,0.0003677361,0.01167646,0.8639322,0.001479206],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5331226,0.0006811311,0.2595276,0.004345306,0.008015059,0.001306558,0.0000264721,0.0003619788,0.1926134],"genre_scores_gemma":[0.9965358,0.0000370049,0.001299129,0.0006868958,0.001101916,0.000004970891,0.000008132136,0.00002480169,0.0003013095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8475999,"threshold_uncertainty_score":0.5229959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01431399069030904,"score_gpt":0.2116769720649777,"score_spread":0.1973629813746687,"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."}}