{"id":"W1995693483","doi":"10.1057/palgrave.rpm.5170118","title":"Learning and pricing in an internet environment with binomial demands","year":2005,"lang":"en","type":"article","venue":"Journal of Revenue and Pricing Management","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Revenue management; Term (time); Revenue; Economics; Dynamic pricing; Computer science; Yield management; Microeconomics; Function (biology); The Internet; Time horizon; Econometrics; Operations research; Finance; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007948395,0.0001442736,0.0002281377,0.0003929108,0.00008445985,0.0001779434,0.000102296,0.00003243565,0.00002586643],"category_scores_gemma":[0.00001058082,0.0001210175,0.00002823867,0.0001461626,0.00003118706,0.000728668,0.0001422367,0.0002519181,0.000003908192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003809062,"about_ca_system_score_gemma":0.000004972217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007833642,"about_ca_topic_score_gemma":0.0001035623,"domain_scores_codex":[0.9990779,0.00002709582,0.0003348202,0.000174696,0.0001911907,0.0001943546],"domain_scores_gemma":[0.9995117,0.00003185564,0.0003292054,0.00008028653,0.00002283284,0.00002416519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001457575,0.00006057482,0.5079335,0.0001525541,0.00003920176,0.0001182379,0.0005357477,0.0004421046,0.0001508442,0.000122399,0.0001220631,0.490177],"study_design_scores_gemma":[0.003321287,0.0003055231,0.7498343,0.001016421,0.0004943741,0.000120193,0.001296772,0.003805429,0.00006416283,0.0002077674,0.2390119,0.0005218487],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973711,0.0005726402,0.0005035051,0.0003276631,0.00006339989,0.0001285234,1.904815e-7,0.000007919286,0.001025096],"genre_scores_gemma":[0.997634,0.0003953192,0.001108713,0.0001999145,0.0003289747,0.000002850107,0.000001210457,0.00001738451,0.000311629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4896551,"threshold_uncertainty_score":0.493495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0090571991764143,"score_gpt":0.2158499429941739,"score_spread":0.2067927438177596,"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."}}