{"id":"W4213008624","doi":"10.2139/ssrn.4032247","title":"Component Pricing with Bundle Size Discount","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Bundle; Component (thermodynamics); Mathematical optimization; Profit (economics); Pricing strategies; Computer science; Economics; Mathematics; Microeconomics","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":[0.0007591577,0.0001318819,0.0001495591,0.00009552285,0.0006166247,0.0006160591,0.0002696672,0.00001320652,0.0002151694],"category_scores_gemma":[0.00001188722,0.0001055281,0.00006821127,0.0001784591,0.00002122693,0.00227783,0.0001730754,0.0008923138,0.00006848952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006939947,"about_ca_system_score_gemma":0.0002852551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002484002,"about_ca_topic_score_gemma":0.0005972027,"domain_scores_codex":[0.9981083,0.000001387043,0.0002071427,0.000154697,0.000220634,0.001307872],"domain_scores_gemma":[0.9996065,0.00001850873,0.000221999,0.0001101744,0.00003003699,0.00001278472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000220508,0.0002856884,0.006065995,0.00001846919,0.0001729235,0.00001324147,0.00004615646,0.005677409,0.00007471305,0.9791183,0.0005260553,0.007780578],"study_design_scores_gemma":[0.002510405,0.0004850174,0.002511191,0.00002754939,0.0001071547,0.0008757288,0.02055569,0.00343546,0.00001003902,0.8529699,0.115687,0.0008247552],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823507,0.0001634727,0.0006951358,0.0005445249,0.0002257471,0.0001000101,8.866162e-7,0.00003854164,0.01588095],"genre_scores_gemma":[0.9974638,0.00003710355,0.00001908756,0.0007799069,0.0005652436,0.000008122081,0.000008845822,0.00002850189,0.001089344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1261483,"threshold_uncertainty_score":0.5940672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006062469888627891,"score_gpt":0.1715245884241588,"score_spread":0.1654621185355309,"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."}}