{"id":"W3205668638","doi":"10.1111/poms.13589","title":"Dynamic Pricing with Money‐Back Guarantees","year":2021,"lang":"en","type":"article","venue":"Production and Operations Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Computer science; Asymptotically optimal algorithm; Mathematical optimization; Dynamic pricing; Product (mathematics); Key (lock); 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":[0.0001917648,0.0001714752,0.0001336727,0.0002332984,0.0004022811,0.0005237857,0.00009176534,0.00002220218,0.0005570435],"category_scores_gemma":[0.00002329041,0.0001499842,0.00003098816,0.0005738999,0.00005313731,0.0009506156,0.0001801327,0.00007538922,0.0002979999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003918037,"about_ca_system_score_gemma":0.000008483534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000446423,"about_ca_topic_score_gemma":0.0003805114,"domain_scores_codex":[0.9988489,0.00001201265,0.0002099606,0.0004932762,0.0002266002,0.0002092515],"domain_scores_gemma":[0.9994527,0.000003049115,0.00004765078,0.0003294572,0.0001540357,0.00001314587],"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":[0.0002219074,0.001901523,0.01235099,0.003761262,0.001204325,0.0002784384,0.001066761,0.06917085,0.00275039,0.7131385,0.08810551,0.1060495],"study_design_scores_gemma":[0.001688119,0.00004912762,0.01664593,0.0003693353,0.0004440761,0.00004110928,0.008401635,0.07067624,0.0006680476,0.001572444,0.8983667,0.001077261],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4366445,0.002041753,0.0454217,0.07104165,0.004122359,0.003945271,0.000004522581,0.0009871273,0.4357911],"genre_scores_gemma":[0.9434749,0.0004087952,0.006479172,0.003659431,0.0004516639,0.0001325657,0.00009138174,0.00003868061,0.04526339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8102611,"threshold_uncertainty_score":0.6116177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01137957012964968,"score_gpt":0.2104599206325693,"score_spread":0.1990803505029196,"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."}}