{"id":"W3123503270","doi":"","title":"Trade-in and Save: A Two-period Closed-loop Supply Chain Game with Price and Technology Dependent Returns","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Stackelberg competition; Supply chain; Competition (biology); Quality (philosophy); Function (biology); Business; Industrial organization; Microeconomics; Rate of return; Economics; Marketing","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":[0.002486049,0.001443261,0.002057076,0.0006423925,0.001159345,0.003320953,0.002279333,0.00468043,0.008339516],"category_scores_gemma":[0.005191998,0.0008430033,0.001250452,0.0006579407,0.002726551,0.004128657,0.001878559,0.002373956,0.0005366885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00323005,"about_ca_system_score_gemma":0.001958904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006276284,"about_ca_topic_score_gemma":0.004445397,"domain_scores_codex":[0.9985966,0.0005878353,0.00006323273,0.0002594147,0.0001334283,0.0003594992],"domain_scores_gemma":[0.9958302,0.002447792,0.0006585495,0.0001973145,0.0001730864,0.0006930318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00240113,0.0008379611,0.003425762,0.0003308168,0.0002509849,0.002404372,0.0008542037,0.7323023,0.007346424,0.2343959,0.002230426,0.01321964],"study_design_scores_gemma":[0.0004148447,0.0006603494,0.0007785471,0.00003427552,0.00009150743,0.0001889765,0.0002899438,0.9106399,0.0006709128,0.08502389,0.0011117,0.00009509852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.654882,0.0003560546,0.3038714,0.00329912,0.0001238729,0.0007195356,0.0007893923,0.0002272252,0.03573131],"genre_scores_gemma":[0.9857961,0.000158163,0.007677309,0.0001299969,0.00002537438,0.0001793739,0.00006371621,0.00001464391,0.005955413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008339516,"threshold_uncertainty_score":0.02789849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01735241862240781,"score_gpt":0.2585010411215967,"score_spread":0.2411486224991889,"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."}}