{"meta":{"query_hash":"61ea4fae75d2","filters":{"venue":"International Journal of Revenue Management"},"cohort_total":5,"direct_labels_cover":0,"predictions_cover":5,"exported":5,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/61ea4fae75d2","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Revenue+Management"},"results":[{"id":"W1972022901","doi":"10.1504/ijrm.2009.024160","title":"Optimal pricing and inventory decisions when individual customer preferences are explicitly modelled","year":2009,"lang":"en","type":"article","venue":"International Journal of Revenue Management","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Revenue management; Inventory management; Economics; Business; Operations research; Marketing; Microeconomics; Operations management; Revenue; Mathematics; Finance","score_opus":0.04399029422153494,"score_gpt":0.27390711253279704,"score_spread":0.2299168183112621,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972022901","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2489675,0.0010900099,0.71755666,0.0038384378,0.00012737037,0.00016607935,0.0004412484,0.00018490103,0.027627831],"genre_scores_gemma":[0.9565389,0.0006807309,0.035555083,0.00016766785,0.00009585056,0.0000733538,0.00015339184,0.000049759066,0.0066852104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976757,0.001278079,0.0000754928,0.00033402763,0.00023232115,0.00040438704],"domain_scores_gemma":[0.9941907,0.0045718416,0.00046572136,0.0003100844,0.00024543874,0.00021620434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004757762,0.0008902221,0.0017928607,0.00066514645,0.0004980913,0.0033453496,0.0017035811,0.002442126,0.004548119],"category_scores_gemma":[0.014339793,0.0013924469,0.0010797293,0.0012824641,0.0018646884,0.0070896014,0.0010356392,0.0026305916,0.00050729944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022011648,0.00015744314,0.0022920691,0.0000991647,0.00008532169,0.0003176224,0.00031529207,0.7015843,0.0006564051,0.2785131,0.0013416798,0.014417473],"study_design_scores_gemma":[0.000020452804,0.000032232183,0.0007450616,0.000014675204,0.000022459863,0.000050095256,0.00010323766,0.83870184,0.00019921377,0.159379,0.00070338073,0.00002832334],"about_ca_topic_score_codex":0.006413701,"about_ca_topic_score_gemma":0.0057963817,"teacher_disagreement_score":0.006413701,"about_ca_system_score_codex":0.0025172757,"about_ca_system_score_gemma":0.0015220874,"threshold_uncertainty_score":0.025161743},"labels":[],"label_agreement":null},{"id":"W1975811972","doi":"10.1504/ijrm.2008.018177","title":"An airline revenue management pricing game with seat allocation","year":2008,"lang":"en","type":"article","venue":"International Journal of Revenue Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Revenue management; Microeconomics; Competition (biology); Economics; Nash equilibrium; Revenue; Yield management; Dynamic pricing; Game theory; Business; Operations research; Finance","score_opus":0.014618539113384022,"score_gpt":0.23412896165786576,"score_spread":0.21951042254448175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975811972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48928675,0.0006597923,0.41482407,0.0019717934,0.00019086686,0.00046441553,0.00058259536,0.0002489765,0.09177075],"genre_scores_gemma":[0.9792884,0.00013738991,0.0126573015,0.00008295954,0.00005053593,0.0000862345,0.000067055946,0.000014619703,0.0076155155],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854434,0.00078514166,0.000029043722,0.00017059542,0.00021823087,0.0002527359],"domain_scores_gemma":[0.9991359,0.0004782973,0.00011043467,0.000038021994,0.00007924699,0.00015814148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001192037,0.0010184078,0.0010748038,0.0003307488,0.0006715872,0.0015285282,0.0012751227,0.001937374,0.0054843854],"category_scores_gemma":[0.0019132594,0.00039008178,0.00054994004,0.0005811005,0.0010858467,0.002446818,0.0011510979,0.0012868146,0.00033183335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069949543,0.00035845276,0.0011269206,0.00018575748,0.00009062728,0.0012374287,0.00027905506,0.6742253,0.0062739896,0.29228398,0.0043016467,0.018937446],"study_design_scores_gemma":[0.00015594986,0.0002903572,0.0005359903,0.000011144602,0.00002430498,0.00022446674,0.00010829573,0.9666403,0.0006418118,0.027634071,0.0037019996,0.00003124824],"about_ca_topic_score_codex":0.0038970155,"about_ca_topic_score_gemma":0.0024452226,"teacher_disagreement_score":0.0054843854,"about_ca_system_score_codex":0.0017981285,"about_ca_system_score_gemma":0.0010924179,"threshold_uncertainty_score":0.018347025},"labels":[],"label_agreement":null},{"id":"W2092451802","doi":"10.1504/ijrm.2013.053358","title":"Railway demand forecasting in revenue management using neural networks","year":2013,"lang":"en","type":"article","venue":"International Journal of Revenue Management","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Revenue management; Artificial neural network; Computer science; Demand forecasting; Revenue; Perceptron; Operations research; Multilayer perceptron; Data mining; Artificial intelligence; Engineering; Economics; Finance","score_opus":0.010622776021945297,"score_gpt":0.21486677970988072,"score_spread":0.2042440036879354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092451802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.65148515,0.0022079889,0.33394825,0.0011232952,0.00013816029,0.00006535198,0.00024003176,0.000473051,0.010318687],"genre_scores_gemma":[0.9891755,0.00027711646,0.0088321315,0.000031940883,0.000038623122,0.00001767739,0.000069765236,0.000007692197,0.0015494983],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996474,0.00015229489,0.000020229307,0.000053765933,0.0000765329,0.000049733848],"domain_scores_gemma":[0.99928147,0.0004969583,0.00006147464,0.00001985068,0.00012463743,0.000015723532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009430346,0.00042176523,0.0003960538,0.00035980644,0.00020315191,0.00067485234,0.0004067266,0.00060252956,0.0008324974],"category_scores_gemma":[0.0026820314,0.00024112954,0.00028529862,0.00059464626,0.00020169916,0.0008682383,0.00032189288,0.0005907645,0.00019602932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006156445,0.000047845948,0.00212503,0.000024694344,0.000021114438,0.00003918402,0.000017603857,0.969813,0.00048257387,0.0010648684,0.00026030873,0.026042217],"study_design_scores_gemma":[0.0000012018335,0.0000057972916,0.0003084361,0.000002224064,0.00000228151,0.0000018094934,0.0000039147208,0.99924123,0.000121619276,0.00025298682,0.000057062778,0.0000015065859],"about_ca_topic_score_codex":0.018020777,"about_ca_topic_score_gemma":0.009693396,"teacher_disagreement_score":0.018020777,"about_ca_system_score_codex":0.0007780011,"about_ca_system_score_gemma":0.00039019037,"threshold_uncertainty_score":0.03583175},"labels":[],"label_agreement":null},{"id":"W2339877656","doi":"10.1504/ijrm.2015.073818","title":"Do retailers set optimal prices in the case of the retail gasoline market?","year":2015,"lang":"en","type":"article","venue":"International Journal of Revenue Management","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Gasoline; Oligopoly; Commodity; Competitor analysis; Economics; Panel data; Microeconomics; Set (abstract data type); Business; Financial economics; Econometrics; Marketing; Market economy","score_opus":0.04262899400930919,"score_gpt":0.2862545751620936,"score_spread":0.24362558115278443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2339877656","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89550394,0.0010641776,0.027673362,0.01240063,0.000067126566,0.000097967466,0.0007520258,0.00017537228,0.062265374],"genre_scores_gemma":[0.99620664,0.00025230006,0.0022673942,0.00024516063,0.000026710979,0.000012979648,0.000114591494,0.000015541747,0.0008586493],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99865,0.00044024942,0.000069659836,0.00040123012,0.00016549553,0.00027339152],"domain_scores_gemma":[0.9915479,0.0041263043,0.0019461174,0.0013250008,0.0006269007,0.00042782092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028838206,0.00028255972,0.0014180776,0.0010012825,0.0010594759,0.004807541,0.0020966998,0.0038926643,0.009005054],"category_scores_gemma":[0.025397453,0.0007318133,0.00087497866,0.0014737416,0.0024165923,0.010005434,0.0012019561,0.0022006521,0.0009880074],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013663484,0.0010551256,0.2307972,0.0006362627,0.00070003286,0.0020972514,0.0035647068,0.14600341,0.0025154974,0.52421373,0.018136466,0.06891397],"study_design_scores_gemma":[0.0004185463,0.00013091114,0.0757787,0.00010011084,0.0002019577,0.00059110275,0.0074073197,0.27843675,0.0017222721,0.6254044,0.009613834,0.00019403087],"about_ca_topic_score_codex":0.015240912,"about_ca_topic_score_gemma":0.019618245,"teacher_disagreement_score":0.015240912,"about_ca_system_score_codex":0.0016736009,"about_ca_system_score_gemma":0.0013209267,"threshold_uncertainty_score":0.030304372},"labels":[],"label_agreement":null},{"id":"W2615187459","doi":"10.1504/ijrm.2017.084152","title":"Pricing of excess inventory on Groupon","year":2017,"lang":"en","type":"article","venue":"International Journal of Revenue Management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Western University","funders":"","keywords":"Business; Inventory management; Order (exchange); Microeconomics; Industrial organization; Economics; Operations management; Finance","score_opus":0.027923119975540762,"score_gpt":0.27487771221128837,"score_spread":0.24695459223574762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615187459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90696716,0.0003278828,0.04753796,0.0009611807,0.00009303968,0.00011360542,0.0001360501,0.0001352167,0.043727778],"genre_scores_gemma":[0.99229276,0.00009741073,0.0032742517,0.00004103302,0.000019446747,0.000015886115,0.00002282532,0.000015430722,0.0042209555],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991985,0.00026084957,0.000020459647,0.00012066917,0.00014623097,0.0002532712],"domain_scores_gemma":[0.9974126,0.0015844271,0.00034777707,0.00025004667,0.00013241838,0.0002727207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013175757,0.00074240845,0.00079547404,0.00049013406,0.0008396303,0.0035204496,0.0015487182,0.0018675907,0.009739994],"category_scores_gemma":[0.0042939535,0.0005392486,0.00066808163,0.0004816417,0.0014989633,0.003952367,0.0018940973,0.0010693229,0.00046473506],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040815813,0.0009013691,0.015694601,0.0003577237,0.00016261029,0.00504472,0.0010202011,0.6582783,0.014690802,0.21504828,0.00484605,0.07987375],"study_design_scores_gemma":[0.00009063012,0.0006934848,0.0056907414,0.00006719328,0.000071341026,0.0004674799,0.001025904,0.9137355,0.0036312758,0.07046658,0.0039402577,0.00011963885],"about_ca_topic_score_codex":0.004529322,"about_ca_topic_score_gemma":0.0049543288,"teacher_disagreement_score":0.009739994,"about_ca_system_score_codex":0.0024321433,"about_ca_system_score_gemma":0.0008063187,"threshold_uncertainty_score":0.032583535},"labels":[],"label_agreement":null}]}