{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":130,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":130,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"93faa8a6ec28","filters":{"venue":"Marketing Science"}},"results":[{"id":"W2125178435","doi":"10.1287/mksc.19.1.4.15178","title":"Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids","year":2000,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":1713,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Interactivity; Computer science; Decision aids; Product (mathematics); Set (abstract data type); Process (computing); Marketing; Business; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.008841738164697608,"gpt":0.2630587904505741,"spread":0.2542170522858764,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034493,0.000169234,0.0002000356,0.0004208438,0.0003309208,0.0002241902,0.0006684639,0.00003807417,0.0005519175],"category_scores_gemma":[0.003141184,0.0001266267,0.00006277213,0.001358044,0.0003410887,0.00108298,0.0003734794,0.0002294991,0.00003769677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006652672,"about_ca_system_score_gemma":0.00002594308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001333964,"about_ca_topic_score_gemma":0.00008566487,"domain_scores_codex":[0.9981269,0.0000610937,0.0004123213,0.000430356,0.000594519,0.0003748147],"domain_scores_gemma":[0.9964386,0.002946707,0.0001927299,0.0003630873,0.00004614003,0.00001276185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002049034,0.00006335606,0.1995674,0.00003545644,0.000002604018,0.000008801216,0.00007825927,0.00005840667,0.004433343,0.00001445888,0.00003065793,0.7955023],"study_design_scores_gemma":[0.0005072253,0.0000101623,0.9852927,0.001862837,0.00003374095,0.000003988573,0.0002836191,0.006553786,0.0001355256,0.0001943337,0.004915946,0.0002060788],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939484,0.0001780157,0.0004538471,0.00004170189,0.000376963,0.0002627001,6.808776e-7,0.0000228224,0.004714887],"genre_scores_gemma":[0.9981331,0.00004918698,0.001315278,0.0003512642,0.00006688551,0.000008560745,0.00000102114,0.00001339879,0.00006134047],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7952963,"threshold_uncertainty_score":0.6043109,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2088640816","doi":"10.1287/mksc.1100.0583","title":"Online Display Advertising: Targeting and Obtrusiveness","year":2011,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":827,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Advertising; Targeted advertising; Display advertising; Matching (statistics); Online advertising; Internet privacy; The Internet; Business; Consumer privacy; Advertising research; Marketing; Computer science; Information privacy; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.02274302533557768,"gpt":0.2413226353367493,"spread":0.2185796100011717,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002900877,0.0001613701,0.000145606,0.000275707,0.0005595347,0.0003150253,0.0004083976,0.00003213898,0.0002529906],"category_scores_gemma":[0.001135421,0.0001467453,0.00003339283,0.0009010328,0.0003838329,0.001397184,0.0005279956,0.0001327937,0.00001983087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001804124,"about_ca_system_score_gemma":0.00002664531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000441044,"about_ca_topic_score_gemma":0.00004051139,"domain_scores_codex":[0.9985031,0.00002189791,0.0002378333,0.0004618269,0.0003250592,0.0004502376],"domain_scores_gemma":[0.999342,0.0001119433,0.0001507979,0.0002074953,0.0001579531,0.00002980534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000707639,0.00007235418,0.8524348,0.0001117964,0.000003195867,0.0000222566,0.0002646629,0.000001183307,0.01100914,0.0008839525,0.00009147655,0.1350345],"study_design_scores_gemma":[0.0001769062,0.000003268579,0.9917113,0.0001314152,0.00002959912,0.00000611174,0.0004036953,0.002842729,0.0001877825,0.0001785348,0.004065233,0.000263379],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721602,0.0001291683,0.0001189285,0.00007692785,0.0004172063,0.0001052131,9.836554e-7,0.0001205553,0.02687088],"genre_scores_gemma":[0.997829,0.00001084327,0.001531996,0.0002938551,0.0001881709,0.000004080221,0.000002906611,0.00001613701,0.000123031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1392766,"threshold_uncertainty_score":0.59841,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2147664728","doi":"10.1287/mksc.1060.0254","title":"Zero as a Special Price: The True Value of Free Products","year":2007,"lang":"en","type":"article","venue":"Marketing Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":612,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Zero (linguistics); Value (mathematics); Economics; Microeconomics; Affect (linguistics); Test (biology); Contrast (vision); Perspective (graphical); Set (abstract data type); Marketing; Business; Mathematics; Computer science; Statistics; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.0584662893362493,"gpt":0.3772242976406483,"spread":0.318758008304399,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06653059,0.000145455,0.0002512737,0.0003911998,0.0006249193,0.0005023816,0.004194032,0.00005523466,0.0003052218],"category_scores_gemma":[0.07851387,0.00008671562,0.00009511658,0.003254998,0.001323666,0.0004717166,0.000795167,0.0002056399,0.0002232581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008788468,"about_ca_system_score_gemma":0.0004580683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003523433,"about_ca_topic_score_gemma":0.00002497038,"domain_scores_codex":[0.9950479,0.0001983087,0.0009207035,0.0008255558,0.002455862,0.0005516217],"domain_scores_gemma":[0.9917468,0.00490186,0.0006233159,0.001831475,0.0007432,0.0001533644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002434413,0.0001305415,0.0114626,0.000004757936,0.00000307675,0.0000214206,0.001188656,0.0001397639,0.01226201,0.005673221,0.02059858,0.9482719],"study_design_scores_gemma":[0.0006616609,0.0002448138,0.5622595,0.0001383673,0.00002313185,0.0001395964,0.002982916,0.001409534,0.02391769,0.2464609,0.1611306,0.0006313267],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9075248,0.00002851156,0.0005173541,0.001008044,0.001811889,0.0001840447,0.000006199311,0.00002373686,0.08889546],"genre_scores_gemma":[0.9931737,0.000002631696,0.004687956,0.0001913538,0.0004844644,0.000001789877,1.472228e-7,0.000008032152,0.001449922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9476406,"threshold_uncertainty_score":0.9612032,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2783822938","doi":"10.1287/mksc.2018.1128","title":"Which Healthy Eating Nudges Work Best? A Meta-Analysis of Field Experiments","year":2019,"lang":"en","type":"article","venue":"Marketing Science","topic":"Obesity, Physical Activity, Diet","field":"Medicine","cited_by":497,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of British Columbia; University of Toronto","keywords":"Nudge theory; Meta-analysis; Field (mathematics); Psychology; Work (physics); Economics; Marketing; Computer science; Econometrics; Social psychology; Business; Engineering; Medicine; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05119421545141928,"gpt":0.3496841802644303,"spread":0.298489964813011,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002652229,0.0001413865,0.0008047764,0.0002885652,0.0001304483,0.00004059522,0.0003092074,0.00004372439,0.0006837043],"category_scores_gemma":[0.001735741,0.0001107365,0.0003425196,0.003813345,0.0001274693,0.0002248781,0.0002183749,0.0001841906,0.00003002817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006043322,"about_ca_system_score_gemma":0.0001119836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001355342,"about_ca_topic_score_gemma":0.00001365047,"domain_scores_codex":[0.9977404,0.0001519999,0.0003069691,0.0005227203,0.0008946109,0.0003833043],"domain_scores_gemma":[0.9977865,0.001019534,0.00021416,0.0005782025,0.0002487903,0.0001528233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001495064,0.001623738,0.9783771,0.0001324646,0.005021094,0.000001768991,0.0004092479,0.0001036447,0.01323991,0.0001305592,0.00007720262,0.0007337751],"study_design_scores_gemma":[0.0003114497,0.0004973326,0.9618915,0.00007445288,0.01793608,0.000001289629,0.0004251023,0.003499428,0.0150527,0.00003514934,0.00005363359,0.0002218807],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808984,0.0001527472,0.00002395544,0.001027725,0.00009672858,0.0002337528,0.000001707721,0.00002845458,0.01753648],"genre_scores_gemma":[0.9968159,0.000003381134,0.001969878,0.000480595,0.0000304676,0.00001249565,0.000001178925,0.000008546688,0.0006775621],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01685891,"threshold_uncertainty_score":0.7486082,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2111176582","doi":"10.1287/mksc.20.3.265.9767","title":"Quality Segmentation in Spatial Markets: When Does Cannibalization Affect Product Line Design?","year":2001,"lang":"en","type":"article","venue":"Marketing Science","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":488,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Hong Kong University of Science and Technology; University of British Columbia","keywords":"Cannibalization; Duopoly; Quality (philosophy); Valuation (finance); Market segmentation; Product (mathematics); Monopoly; Business; Price discrimination; Marketing; Oligopoly; Industrial organization; Microeconomics; Economics; Product differentiation","retraction":null,"screen_n_in":null,"score":{"opus":0.02787978298205188,"gpt":0.2595335147239848,"spread":0.2316537317419329,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.006463237,0.0001223908,0.0001268417,0.0002623419,0.0002074646,0.001101664,0.0002666886,0.00002273318,0.0001609135],"category_scores_gemma":[0.001663619,0.00009849772,0.00002363699,0.0006265137,0.0001057438,0.005577529,0.0001251487,0.00005901659,0.00006513012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001255627,"about_ca_system_score_gemma":0.00005049563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001478032,"about_ca_topic_score_gemma":0.0008969178,"domain_scores_codex":[0.9986914,0.00001243516,0.0003125979,0.0004012427,0.0002511654,0.0003311624],"domain_scores_gemma":[0.9993963,0.0001094437,0.0002118856,0.0001754343,0.00009219027,0.00001474149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007829166,0.0002121704,0.7457247,0.0003087086,0.000006725663,0.0000137424,0.0001972042,0.00546158,0.006567324,0.001708137,0.001207264,0.2378095],"study_design_scores_gemma":[0.0008313191,0.00001532644,0.8682771,0.0001470548,0.00001044709,0.000003173207,0.0007745273,0.1180334,0.0009028204,0.008333968,0.002091302,0.0005795674],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693012,0.000008726148,0.004957397,0.0002582407,0.0004251135,0.0003341964,6.894168e-7,0.00006646661,0.024648],"genre_scores_gemma":[0.9976617,0.000005871753,0.001257875,0.0003720346,0.0003333129,0.00001348123,0.00001327945,0.00001011059,0.0003323084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2372299,"threshold_uncertainty_score":0.9999353,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2005512101","doi":"10.1287/mksc.1040.0109","title":"Overchoice and Assortment Type: When and Why Variety Backfires","year":2005,"lang":"en","type":"article","venue":"Marketing Science","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":450,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Regret; Variety (cybernetics); Set (abstract data type); Marketing; Product (mathematics); Product category; Business; Dimension (graph theory); Product type; Advertising; Computer science; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.08857236628370567,"gpt":0.3841716594215719,"spread":0.2955992931378663,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01359187,0.0001292589,0.0001890018,0.0001939982,0.0005131556,0.001230241,0.0006701521,0.00005037021,0.0002981552],"category_scores_gemma":[0.008056256,0.00009652595,0.00002884426,0.0005673089,0.0005810252,0.000827533,0.0005290282,0.0001248618,0.00008663828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007436286,"about_ca_system_score_gemma":0.0001047932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005069781,"about_ca_topic_score_gemma":0.00006038159,"domain_scores_codex":[0.9974266,0.0001335073,0.0004038524,0.0007669132,0.0009358419,0.0003332431],"domain_scores_gemma":[0.9968907,0.002050729,0.0001684362,0.0004651542,0.000220169,0.0002047705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003734626,0.00003108756,0.05598743,0.000001646274,0.000001926652,0.000002696038,0.0003697858,0.00003262695,0.0008519035,0.0001995219,0.01020455,0.9322795],"study_design_scores_gemma":[0.0003879102,0.0001046333,0.5451908,0.00006131407,0.00001807941,0.00006358472,0.0004304774,0.01607381,0.0002851776,0.01997539,0.4169824,0.0004264046],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881569,0.0002137206,0.0001702171,0.001646788,0.0003873436,0.00008472095,0.000004070303,0.00003128163,0.009304964],"genre_scores_gemma":[0.9852279,0.00003850649,0.01285193,0.0008859466,0.00008877938,0.000001925157,2.505215e-7,0.000006372811,0.0008983711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9318531,"threshold_uncertainty_score":0.9998066,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2150317453","doi":"10.1287/mksc.21.3.229.143","title":"Modeling Consumer Demand for Variety","year":2002,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":434,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of Toronto","keywords":"Unobservable; Variety (cybernetics); Product (mathematics); Econometrics; Function (biology); Distribution (mathematics); Mathematics; Mixed logit; Computer science; Statistics; Logistic regression","retraction":null,"screen_n_in":null,"score":{"opus":0.0355794524722642,"gpt":0.2476581412200452,"spread":0.212078688747781,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003930314,0.0001451497,0.0001402158,0.0002345964,0.0009004668,0.0006450833,0.0004323447,0.00003626331,0.0004702538],"category_scores_gemma":[0.001384096,0.0001377955,0.00006909851,0.0007937309,0.0001902313,0.001095843,0.0002013039,0.0001005079,0.00007521945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002313124,"about_ca_system_score_gemma":0.00001764779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001213002,"about_ca_topic_score_gemma":0.00002032464,"domain_scores_codex":[0.998472,0.00001249617,0.0002367742,0.0004394182,0.0003372288,0.0005020821],"domain_scores_gemma":[0.9991815,0.0002030684,0.00008329115,0.0002618314,0.0002477349,0.00002258671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002717874,0.0002799149,0.3527077,0.0008389821,0.00003531268,0.00001723529,0.0004264793,0.003159733,0.01536508,0.007030973,0.01135855,0.6085082],"study_design_scores_gemma":[0.0003508648,0.000002590919,0.01143443,0.00005740252,0.00004827835,0.00000325246,0.00007948413,0.9705402,0.00002735797,0.0002858398,0.01688649,0.0002838164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9242678,0.0002790903,0.01273787,0.0005264028,0.0007593203,0.0003958763,0.000001687566,0.0002326997,0.06079929],"genre_scores_gemma":[0.9969724,0.00001002105,0.001692295,0.0006278494,0.0002421388,0.00002513849,0.000001296631,0.00001681785,0.0004119713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9673805,"threshold_uncertainty_score":0.6925753,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2096473998","doi":"10.1287/mksc.22.1.58.12849","title":"Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation","year":2003,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":376,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Search cost; Sample (material); Set (abstract data type); Quality (philosophy); Economics; Econometric model; Marketing; Econometrics; Business; Advertising; Microeconomics; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.04639560220219047,"gpt":0.2704476989946586,"spread":0.2240520967924681,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003360725,0.00009560892,0.0001092696,0.0002213216,0.0004087285,0.0002786262,0.0001175563,0.00002444205,0.00007013304],"category_scores_gemma":[0.001247837,0.00008675148,0.00001978672,0.0005207249,0.0003118228,0.001419488,0.00009294807,0.00008291832,0.000003008836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002248914,"about_ca_system_score_gemma":0.00007672566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001297922,"about_ca_topic_score_gemma":0.00003368737,"domain_scores_codex":[0.998947,0.00003980193,0.0002205401,0.0002187069,0.0003319869,0.0002420108],"domain_scores_gemma":[0.9992667,0.0001664017,0.0001388302,0.0001385765,0.0002730848,0.0000163547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003013253,0.0000476811,0.6894666,0.001273711,0.00001872528,0.000005718708,0.002118615,0.009829142,0.1764182,0.04511798,0.0006751855,0.07472716],"study_design_scores_gemma":[0.0004808959,0.000004594572,0.09077512,0.00008711238,0.00003564662,0.00001325833,0.0007992678,0.9040839,0.001536371,0.001497026,0.0004166665,0.0002701324],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859483,0.00003865116,0.0008446043,0.00008787775,0.00008188692,0.0001599813,0.000001830931,0.00003128277,0.01280563],"genre_scores_gemma":[0.9985614,0.000004724262,0.001218442,0.0001497017,0.00001442081,0.00000322873,0.000002495284,0.000005178733,0.00004041244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8942547,"threshold_uncertainty_score":0.3537623,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3123680844","doi":"10.1287/mksc.2014.0900","title":"Product and Pricing Decisions in Crowdfunding","year":2015,"lang":"en","type":"article","venue":"Marketing Science","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":302,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Product (mathematics); Product line; Quality (philosophy); Business; Marketing; Mechanism (biology); Pricing strategies; Dynamic pricing; Microeconomics; New product development; Industrial organization; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.03618739147010243,"gpt":0.25757689650104,"spread":0.2213895050309376,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006206766,0.000142964,0.0001490536,0.0006811704,0.0003141269,0.001008384,0.0004518604,0.00002414266,0.000006917861],"category_scores_gemma":[0.01595192,0.0001356463,0.00001800724,0.002722406,0.0003557629,0.002917,0.0006554536,0.0001482767,0.00006234159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001157436,"about_ca_system_score_gemma":0.0001043693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002022211,"about_ca_topic_score_gemma":0.00008329561,"domain_scores_codex":[0.9981558,0.00001078917,0.0002621935,0.0005762552,0.0004776494,0.0005173206],"domain_scores_gemma":[0.9992259,0.0001787328,0.0001496465,0.0002374173,0.0001770409,0.00003126936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007400743,0.00006410864,0.8655735,0.00007801374,0.000001884416,0.00004051252,0.000205546,0.0001462874,0.007872375,0.01924399,0.002128865,0.104571],"study_design_scores_gemma":[0.0006582473,0.00001446731,0.9395301,0.0008844985,0.000008280036,0.00002801566,0.0007185673,0.02031845,0.0007082713,0.008607297,0.02785656,0.0006672022],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9105895,0.0001121211,0.0003039817,0.0005009032,0.0003751541,0.000171085,2.598336e-7,0.0001028984,0.08784416],"genre_scores_gemma":[0.9972554,0.000004106393,0.001954345,0.0002316299,0.0001904387,0.000008184097,5.734719e-7,0.0000148024,0.0003405447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1039038,"threshold_uncertainty_score":0.9923371,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3123243604","doi":"10.1287/mksc.2017.1051","title":"Changing Their Tune: How Consumers’ Adoption of Online Streaming Affects Music Consumption and Discovery","year":2017,"lang":"en","type":"article","venue":"Marketing Science","topic":"Copyright and Intellectual Property","field":"Business, Management and Accounting","cited_by":273,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Hyderabad Eye Research Foundation; University of British Columbia","keywords":"Active listening; Consumption (sociology); Music industry; Early adopter; Digital audio; Purchasing; Diversity (politics); Set (abstract data type); Advertising; Business; Computer science; Marketing; Telecommunications; Psychology; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.03567042852066848,"gpt":0.2389141279069903,"spread":0.2032436993863218,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001803348,0.0001291325,0.0001493829,0.0002857198,0.001087075,0.001311158,0.0003602016,0.00003000356,0.00007514809],"category_scores_gemma":[0.001909607,0.00009543072,0.0000339264,0.0002229466,0.0007427986,0.003391537,0.0004693122,0.0000901342,0.000007031848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002082849,"about_ca_system_score_gemma":0.00002574845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007932508,"about_ca_topic_score_gemma":0.00007725487,"domain_scores_codex":[0.9990216,0.00001571173,0.0001124,0.0003196886,0.0002349127,0.000295653],"domain_scores_gemma":[0.9991178,0.0001384885,0.0003098808,0.0002938644,0.0001262202,0.00001377107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002788123,0.0001713178,0.2481963,0.001395109,0.00003079271,0.000008791455,0.0008383387,0.000004504123,0.2739629,0.001108532,0.00149952,0.4725051],"study_design_scores_gemma":[0.0005953605,0.00002757288,0.865542,0.001129581,0.00004498577,0.000005785059,0.001721352,0.1228516,0.005322227,0.0001542922,0.002165306,0.0004399813],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923753,0.00009451967,0.0002207625,0.0003361591,0.0003560785,0.000154211,0.000002529705,0.00003847612,0.006422002],"genre_scores_gemma":[0.9991981,0.00003499743,0.0001270783,0.00009548086,0.0001890941,0.000002603091,0.000005104263,0.000009069729,0.0003384432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6173458,"threshold_uncertainty_score":0.9997256,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3122176968","doi":"10.1287/mksc.2014.0890","title":"Social Dollars: The Economic Impact of Customer Participation in a Firm-Sponsored Online Customer Community","year":2015,"lang":"en","type":"article","venue":"Marketing Science","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":269,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Business; Marketing; Interpersonal ties; Liberian dollar; Customer retention; Online community; Entertainment; User-generated content; Customer to customer; Advertising; Social media; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.06975585888862677,"gpt":0.404066791103345,"spread":0.3343109322147182,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0258463,0.0001129332,0.0002110436,0.0001570164,0.0009451435,0.0001697097,0.0008149067,0.0000759297,0.00003515498],"category_scores_gemma":[0.01354379,0.00008830209,0.00009509418,0.001140139,0.002306043,0.0004601933,0.0001572445,0.0002985502,0.00002816583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001188183,"about_ca_system_score_gemma":0.002028372,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01156415,"about_ca_topic_score_gemma":0.004667854,"domain_scores_codex":[0.9957894,0.00252056,0.0003473533,0.0001869352,0.0006175024,0.0005382643],"domain_scores_gemma":[0.9974525,0.001720606,0.0002294586,0.000215206,0.0002073294,0.0001749077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000888592,0.000590026,0.6651593,0.00003356292,0.00003511472,0.000004234046,0.2657992,0.001214334,0.0004987309,0.003662552,0.006413527,0.05570078],"study_design_scores_gemma":[0.0005198321,0.00006082693,0.9495004,0.00006590248,0.00001315998,4.909282e-7,0.04377387,0.001189521,0.00001912489,0.0006871797,0.003925179,0.0002444657],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9056682,0.00001689708,8.165519e-7,0.0004433568,0.0002381533,0.0001693707,0.00001188877,0.00003589103,0.09341545],"genre_scores_gemma":[0.9994554,0.000007668264,0.00005663599,0.0000465312,0.0001649355,0.00001152761,0.000002728925,0.000007931924,0.0002466254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2843411,"threshold_uncertainty_score":0.9950179,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2124082999","doi":"10.1287/mksc.1030.0043","title":"Own-Brand and Cross-Brand Retail Pass-Through","year":2005,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":237,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kellogg's (Canada)","funders":"University of Chicago","keywords":"Demand curve; Product (mathematics); Odds; Business; Product category; Private label; Market power; Function (biology); Economics; Marketing; Econometrics; Advertising; Microeconomics; Mathematics; Logistic regression; Statistics; Monopoly","retraction":null,"screen_n_in":null,"score":{"opus":0.02069744150291307,"gpt":0.2695681682736955,"spread":0.2488707267707824,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004063743,0.0001921498,0.0001805784,0.000194312,0.0009862585,0.001616894,0.0004297946,0.00004913271,0.0007315458],"category_scores_gemma":[0.001015433,0.0001726826,0.00004649519,0.0009397718,0.0006643828,0.003042493,0.0003957209,0.0001715587,0.000111627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002841973,"about_ca_system_score_gemma":0.00004143036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000180801,"about_ca_topic_score_gemma":0.000085223,"domain_scores_codex":[0.9980865,0.00002286517,0.000293484,0.0005712938,0.0004803981,0.0005454281],"domain_scores_gemma":[0.9991243,0.000213085,0.0001588441,0.0003079153,0.0001663867,0.00002950791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000107357,0.00002987793,0.7544335,0.0001001429,0.000004106055,0.000007860695,0.0001241808,0.00001122339,0.005024486,0.000458204,0.0009825552,0.2387165],"study_design_scores_gemma":[0.0006084459,0.00000342611,0.7974928,0.00008042622,0.00003139664,0.00001028458,0.00006807551,0.002715279,0.0001933614,0.0001653403,0.1982991,0.0003320871],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8772875,0.000241979,0.00007338946,0.001064947,0.0002822915,0.0001368702,9.272869e-7,0.0001286186,0.1207835],"genre_scores_gemma":[0.9955128,0.00002427917,0.0009154432,0.001153216,0.000472604,0.00000789652,0.000001583313,0.00001726931,0.001894897],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2383844,"threshold_uncertainty_score":0.9994195,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2108955129","doi":"10.1287/mksc.1050.0176","title":"Market Entry and Consumer Behavior: An Investigation of a Wal-Mart Supercenter","year":2006,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":197,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Revenue; Business; Advertising; Quarter (Canadian coin); Marketing; Product (mathematics); Barriers to entry; Grocery store; Consumer behaviour; Profiling (computer programming); Market share; Market structure; Industrial organization; Finance; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01315045321001472,"gpt":0.2291572289053217,"spread":0.216006775695307,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003038139,0.0001582442,0.0001631279,0.0003553039,0.0003335252,0.0003609818,0.000285141,0.00004423262,0.0004100303],"category_scores_gemma":[0.0001973012,0.0001530487,0.00003504324,0.0006865291,0.0006817203,0.001547875,0.0002320523,0.0001055921,0.000008143531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000212963,"about_ca_system_score_gemma":0.00004243033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001444805,"about_ca_topic_score_gemma":0.0001740414,"domain_scores_codex":[0.998435,0.0000478722,0.000324567,0.0004242737,0.0004204412,0.000347824],"domain_scores_gemma":[0.9992304,0.0001213538,0.0001597098,0.0002692379,0.0001902021,0.00002913697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003607078,0.00003215332,0.9575641,0.00006535899,0.000001137704,0.00000370674,0.0000303137,4.185386e-7,0.02980013,0.0001421537,0.0007523454,0.01157217],"study_design_scores_gemma":[0.0002598802,0.000004670899,0.9960293,0.00007913179,0.00005319987,0.000005162806,0.0001219735,0.00128064,0.0003370053,0.0001009705,0.001537567,0.000190553],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789343,0.00006930355,0.0000102892,0.0001122453,0.0002149821,0.0001930073,0.000002477441,0.00007045479,0.02039296],"genre_scores_gemma":[0.9988791,0.000006639543,0.0004462123,0.0001931731,0.0001290758,0.00001318451,0.000008473676,0.00001405304,0.0003100722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0384652,"threshold_uncertainty_score":0.6241144,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2116975071","doi":"10.1287/mksc.20.4.405.9756","title":"Pizzas: π or Square? Psychophysical Biases in Area Comparisons","year":2001,"lang":"en","type":"article","venue":"Marketing Science","topic":"Color perception and design","field":"Psychology","cited_by":180,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Salience (neuroscience); Dimension (graph theory); Context (archaeology); Salient; Econometrics; Cognitive psychology; Social psychology; Psychology; Mathematics; Computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.1333088345807083,"gpt":0.4020725030668341,"spread":0.2687636684861258,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002071193,0.0001158997,0.0001575663,0.000270012,0.0002154658,0.00008801075,0.0004058645,0.00004591975,0.006596371],"category_scores_gemma":[0.0009123473,0.00009539394,0.00004130617,0.001720391,0.0004329003,0.000127843,0.00005424313,0.0001725899,0.0006751711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007326301,"about_ca_system_score_gemma":0.00008891046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001289251,"about_ca_topic_score_gemma":0.00022735,"domain_scores_codex":[0.9981886,0.0002369843,0.0002361303,0.0004950991,0.0003138139,0.0005293331],"domain_scores_gemma":[0.9986354,0.00075983,0.0000587925,0.0003581747,0.00004835735,0.0001394832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004454318,0.002366604,0.7072856,0.0000188201,0.0000124374,0.0003956477,0.006800775,0.0003052426,0.01747989,0.001340845,0.1299296,0.1296102],"study_design_scores_gemma":[0.0005184399,0.0000902009,0.9794026,0.00006530819,0.000002731752,0.00004372305,0.001852761,0.003595934,0.00001200034,0.00003354573,0.01420903,0.0001737418],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8678358,0.00001800832,0.0003901694,0.0005267329,0.0004830929,0.0001375414,0.000001564017,0.0000938294,0.1305132],"genre_scores_gemma":[0.9948596,0.000006954675,0.0005695889,0.0005536255,0.00007676469,0.00002983223,8.72977e-7,0.000007980783,0.003894763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.272117,"threshold_uncertainty_score":0.9943117,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1872399634","doi":"10.1287/mksc.2015.0926","title":"The Economic Value of Online Reviews","year":2015,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":180,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Counterfactual thinking; Quality (philosophy); Product (mathematics); Value (mathematics); Marketing; Variance (accounting); Set (abstract data type); Reading (process); Population; Computer science; Advertising; Business; Psychology; Machine learning; Mathematics; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.04022442503184156,"gpt":0.2847558215303389,"spread":0.2445313964984973,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01124157,0.00008523926,0.0001302749,0.0001067972,0.0003068741,0.0002433459,0.0006411446,0.00001413463,0.00003926505],"category_scores_gemma":[0.002264626,0.00005773752,0.00004509287,0.0004625716,0.000322458,0.0005419275,0.0003128705,0.00007412619,0.00007594054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004884015,"about_ca_system_score_gemma":0.0001361716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004234214,"about_ca_topic_score_gemma":0.0001223192,"domain_scores_codex":[0.9989945,0.00003628123,0.0002949674,0.0002038858,0.0002254367,0.0002449776],"domain_scores_gemma":[0.9991164,0.0001986665,0.0002489747,0.0003090153,0.0001095279,0.00001739339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001131095,0.00004134431,0.3244636,0.0001252378,0.000005124783,0.000002305306,0.00009606877,0.0001050613,0.002207302,0.007122673,0.01287841,0.6528398],"study_design_scores_gemma":[0.0002891623,0.000006132327,0.3467456,0.0001540614,0.00004054558,0.000003188521,0.0003759527,0.01898296,0.0000738958,0.0006475747,0.6324329,0.0002480351],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9370407,0.000715663,0.00002375647,0.0007082532,0.0009169547,0.0001775342,8.314498e-7,0.00003796371,0.06037828],"genre_scores_gemma":[0.9985542,0.00006314613,0.0004085054,0.0002633089,0.00029118,0.00000490185,0.000001152831,0.000007587663,0.0004060753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6525917,"threshold_uncertainty_score":0.3896127,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2168789360","doi":"10.1287/mksc.1090.0486","title":"Information Provision in a Vertically Differentiated Competitive Marketplace","year":2009,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":168,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Incentive; Quality (philosophy); Monopoly; Competition (biology); Preference; Product (mathematics); Business; Microeconomics; Marketing; Product differentiation; Economics; Industrial organization; Private information retrieval; Strategic complements; Computer science; Cournot competition","retraction":null,"screen_n_in":null,"score":{"opus":0.007520381268386825,"gpt":0.2246920262876693,"spread":0.2171716450192825,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003100261,0.0001368711,0.0001356693,0.0005777481,0.0002647766,0.0006697279,0.0003709975,0.00003607023,0.0001859175],"category_scores_gemma":[0.001585917,0.0001257567,0.00003227161,0.001598234,0.0001233745,0.00304383,0.0001601499,0.0001608058,0.00008356932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006086983,"about_ca_system_score_gemma":0.00005183376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001057462,"about_ca_topic_score_gemma":0.00003727902,"domain_scores_codex":[0.998557,0.00003319523,0.0003113139,0.0002159666,0.0004722282,0.0004103417],"domain_scores_gemma":[0.9993507,0.0001321773,0.0001250976,0.0001849161,0.0001872083,0.00001990068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007596503,0.0001851677,0.4714552,0.0001240265,0.000002757114,0.00001316165,0.0003147685,0.00001970271,0.01179952,0.007667934,0.0004430966,0.507215],"study_design_scores_gemma":[0.0003985909,0.000007686583,0.9843517,0.0001580577,0.000008822695,0.000001523442,0.000211828,0.01205053,0.0000557604,0.0002034429,0.002370547,0.0001815271],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8915337,0.000009122768,0.0001658597,0.0006635411,0.0001800149,0.0002310445,4.512633e-7,0.0001134508,0.1071028],"genre_scores_gemma":[0.9988091,0.000002454627,0.0001864499,0.0008912503,0.00004476187,0.000005107917,0.000005967438,0.000004240385,0.0000506929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5128965,"threshold_uncertainty_score":0.6458201,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2102752180","doi":"10.1287/mksc.2013.0805","title":"<b>Invited Paper</b>—Learning Models: An Assessment of Progress, Challenges, and New Developments","year":2013,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":143,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Brand loyalty; Loyalty; Identification (biology); Discrete choice; Product (mathematics); Consumer choice; Data science; Marketing; Machine learning; Business; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05850024394671744,"gpt":0.2874395728927435,"spread":0.2289393289460261,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003047648,0.0001678125,0.0001848661,0.0003016132,0.0003640621,0.0004445544,0.0003964086,0.00004022617,0.0001199563],"category_scores_gemma":[0.0002793465,0.0001541065,0.00002292873,0.0005890116,0.0002583797,0.00348646,0.0004227935,0.0001589151,0.000005244243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002598835,"about_ca_system_score_gemma":0.00007388635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004998904,"about_ca_topic_score_gemma":0.00003917795,"domain_scores_codex":[0.9982594,0.00004601984,0.0002924614,0.0004719081,0.0005243684,0.0004057991],"domain_scores_gemma":[0.9991597,0.00009235048,0.0002334958,0.0002197066,0.0002414438,0.00005329689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000009349362,0.00004027854,0.2189782,0.0001193182,0.00000460718,0.00000149565,0.0001661108,0.00001764766,0.00226545,0.0005938864,0.00009432322,0.7777094],"study_design_scores_gemma":[0.0002381471,0.000008932201,0.9531413,0.0001503206,0.00001790568,0.000002009439,0.0004627287,0.04251806,0.00001422448,0.0006037438,0.002617602,0.0002250531],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9739621,0.0007379615,0.0001043105,0.001129725,0.000140857,0.0003109446,1.366021e-7,0.0001345446,0.02347947],"genre_scores_gemma":[0.9904191,0.0001260539,0.008956494,0.0003091208,0.00007829013,0.00001934869,0.000002704405,0.00001731942,0.00007150984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7774844,"threshold_uncertainty_score":0.6284279,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2131752029","doi":"10.1287/mksc.1060.0260","title":"Brand Effects on Choice and Choice Set Formation Under Uncertainty","year":2007,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":140,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Credibility; Consumer choice; Choice set; Preference; Context (archaeology); Brand equity; Set (abstract data type); Economics; Econometrics; Willingness to pay; Marketing; Microeconomics; Business; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01833136050300218,"gpt":0.2701840257648551,"spread":0.251852665261853,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005767957,0.0001501963,0.0001197874,0.0003564148,0.0006788743,0.0005484341,0.0002511829,0.00003944827,0.00004075856],"category_scores_gemma":[0.001816081,0.0001339846,0.00002782685,0.000964739,0.00016138,0.001385984,0.000173469,0.0001475723,0.00002783839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005073797,"about_ca_system_score_gemma":0.00001830445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004994529,"about_ca_topic_score_gemma":0.0003593945,"domain_scores_codex":[0.9985468,0.00002491701,0.0001985825,0.0003482394,0.0004358512,0.0004456502],"domain_scores_gemma":[0.9981458,0.001376671,0.0001386265,0.0001974156,0.0001108355,0.00003060946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001432884,0.00003676446,0.5302557,0.0004646379,0.000005458844,0.000007287529,0.0001187169,0.00009738535,0.01759663,0.0006241593,0.0008426184,0.4498073],"study_design_scores_gemma":[0.0004376143,0.000007294013,0.9831563,0.0001551053,0.00002351171,0.000003029031,0.00009523107,0.004553469,0.0003168737,0.0001033505,0.01093792,0.0002102481],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9724829,0.00004194713,0.0004501945,0.0003437297,0.0003765741,0.000204383,3.99865e-7,0.0001010726,0.02599883],"genre_scores_gemma":[0.9978206,0.000002962267,0.00009018342,0.001614407,0.0003191972,0.000004066831,0.000002991826,0.0000101918,0.0001354707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4529006,"threshold_uncertainty_score":0.5463735,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2137442203","doi":"10.1287/mksc.1030.0035","title":"The Shape of Advertising Response Functions Revisited: A Model of Dynamic Probabilistic Thresholds","year":2004,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":136,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Econometrics; Competitor analysis; Flexibility (engineering); Advertising; Threshold model; Economics; Probabilistic logic; Function (biology); Order (exchange); Mathematics; Marketing; Statistics; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.01586705206406209,"gpt":0.2491785002214051,"spread":0.233311448157343,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007799949,0.0001231236,0.0001585422,0.0002755957,0.0007067733,0.0001772956,0.0005497137,0.00002939416,0.00002870916],"category_scores_gemma":[0.003941927,0.00009399646,0.00007445392,0.001568023,0.000665014,0.0006170946,0.0002984839,0.0001217957,0.000005667964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000660712,"about_ca_system_score_gemma":0.0001919441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009498562,"about_ca_topic_score_gemma":0.00005068092,"domain_scores_codex":[0.9984277,0.00003902385,0.0004035177,0.0003070133,0.0004996759,0.0003230413],"domain_scores_gemma":[0.9984214,0.0004765163,0.0003026049,0.000425116,0.0003595448,0.00001479885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.004936137,0.000373971,0.1416051,0.001531561,0.00003753237,0.0000108228,0.0006438949,0.02805151,0.5550159,0.009823694,0.0001715403,0.2577983],"study_design_scores_gemma":[0.0006569588,0.00002305316,0.5208519,0.001124742,0.0001401406,0.000007712494,0.0005109434,0.472339,0.000245443,0.003354898,0.000371481,0.0003737139],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992762,0.0001304023,0.0008837853,0.0003988091,0.0001356199,0.0002157871,0.000002429915,0.00004876222,0.005422428],"genre_scores_gemma":[0.9991703,0.000008066996,0.0005646003,0.0000619645,0.00002084431,0.000008149472,8.707464e-7,0.0000114069,0.0001537902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5547705,"threshold_uncertainty_score":0.5436,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2131467577","doi":"10.1287/mksc.1050.0129","title":"Coupons Versus Rebates","year":2007,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":134,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Reservation; Product (mathematics); Business; Key (lock); Attractiveness; Advertising; Payment; Control (management); Significant difference; Microeconomics; Computer science; Marketing; Economics; Computer security; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.02443028066838856,"gpt":0.2711090965371489,"spread":0.2466788158687604,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009561181,0.0001194023,0.00009699909,0.0003778334,0.0006456512,0.0004616654,0.0004916808,0.000028576,0.0003752705],"category_scores_gemma":[0.002142326,0.0001135706,0.00004088305,0.00159619,0.0003106156,0.0009601449,0.0002886217,0.0001233479,0.0001701477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000393597,"about_ca_system_score_gemma":0.00004114901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002501286,"about_ca_topic_score_gemma":0.0001529944,"domain_scores_codex":[0.9984212,0.000008342542,0.0002025321,0.0003457359,0.0004678303,0.0005543599],"domain_scores_gemma":[0.998947,0.0004816884,0.0001122257,0.00026021,0.0001747615,0.00002410977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008895601,0.00007226867,0.6110366,0.00008830303,0.000007903517,0.00005620205,0.00009057249,0.00000738022,0.03339339,0.005038521,0.002435368,0.3468839],"study_design_scores_gemma":[0.0005010598,0.000005421782,0.9361567,0.0000539714,0.00003219338,0.000003105809,0.0003812166,0.001160927,0.0004662248,0.000109348,0.06081272,0.0003171453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7453761,0.00003392081,0.0001416313,0.0002044285,0.001121013,0.00007378143,2.132804e-7,0.0001530783,0.2528958],"genre_scores_gemma":[0.9984981,0.000002026626,0.0004684151,0.000304202,0.000359196,0.000001997096,0.000001199761,0.00001126693,0.0003536392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3465668,"threshold_uncertainty_score":0.4965892,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2155617681","doi":"10.1287/mksc.1060.0238","title":"Cross-Market Network Effect with Asymmetric Customer Loyalty: Implications for Competitive Advantage","year":2007,"lang":"en","type":"article","venue":"Marketing Science","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":133,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Wharton School, University of Pennsylvania; University of British Columbia","keywords":"Loyalty business model; Business; Profit (economics); Marketing; Competitive advantage; Disadvantage; Customer base; Newspaper; Industrial organization; Market share analysis; Network effect; First-mover advantage; Monopolistic competition; Microeconomics; Advertising; Economics; Order (exchange); Market microstructure; Computer science; Monopoly","retraction":null,"screen_n_in":null,"score":{"opus":0.008143510651403375,"gpt":0.2522562940688977,"spread":0.2441127834174943,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.006860425,0.0001666486,0.0001774796,0.0003176255,0.0007398097,0.00157267,0.000439226,0.0000340822,0.00005306845],"category_scores_gemma":[0.0008391464,0.0001330069,0.0000583743,0.001729319,0.0003488011,0.003569119,0.0001780717,0.00008572965,0.0001002265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007431296,"about_ca_system_score_gemma":0.00003605911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001867949,"about_ca_topic_score_gemma":0.0000498806,"domain_scores_codex":[0.9984255,0.000001740647,0.0002484371,0.0004367901,0.0001665668,0.0007209858],"domain_scores_gemma":[0.998455,0.0008191707,0.0002308947,0.0002423942,0.0002160805,0.00003643776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005363375,0.00004458627,0.8516807,0.0001455947,0.00001444661,0.000002571386,0.000005858811,0.0003311036,0.00005456794,0.07446755,0.00227429,0.07044237],"study_design_scores_gemma":[0.0006886123,0.00004171362,0.9320441,0.00008489482,0.00002412309,0.000005756176,0.0001280896,0.003203297,0.00003809043,0.001313129,0.06202433,0.0004039069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4536777,0.00001413523,0.001472782,0.00005239477,0.0002370787,0.0003445243,0.000003199866,0.00007832392,0.5441199],"genre_scores_gemma":[0.9965761,0.000001429537,0.001485488,0.0006585924,0.0005374689,0.00002504282,0.00001152619,0.00002198764,0.0006823873],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5434375,"threshold_uncertainty_score":0.9994638,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4391220979","doi":"10.1287/mksc.2023.0454","title":"Frontiers: Determining the Validity of Large Language Models for Automated Perceptual Analysis","year":2024,"lang":"en","type":"article","venue":"Marketing Science","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":131,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Perception; Computer science; Data science; Human language; Natural language processing; Language model; Artificial intelligence; Cognitive psychology; Machine learning; Econometrics; Economics; Psychology; Linguistics","retraction":null,"screen_n_in":null,"score":{"opus":0.04878391879767375,"gpt":0.4075470857221072,"spread":0.3587631669244334,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01630735,0.00006390642,0.0001501737,0.0002763127,0.0008360062,0.0002334918,0.0004600353,0.00002654893,0.00005640084],"category_scores_gemma":[0.002301138,0.00004507177,0.0001952221,0.002911232,0.000483462,0.000288195,0.00007410417,0.00005758837,0.000001335922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006002837,"about_ca_system_score_gemma":0.0002310021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001471048,"about_ca_topic_score_gemma":0.0001720601,"domain_scores_codex":[0.9982141,0.0004795403,0.0001880457,0.0002735005,0.0005704641,0.0002743751],"domain_scores_gemma":[0.9977688,0.001780049,0.00006709395,0.0001290827,0.0002031853,0.0000518484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009320002,0.0003063875,0.1306297,0.0002662795,0.001199715,0.00001141606,0.3754472,0.05558162,0.002863087,0.06064278,0.01003861,0.3629201],"study_design_scores_gemma":[0.00003841783,0.000006407776,0.02677472,0.00001396792,0.0001849045,7.511179e-8,0.007862331,0.9633987,0.00002259775,0.0008911893,0.0007392697,0.00006741362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7531711,0.0001464237,0.2401451,0.0004182319,0.0003096164,0.0001473324,0.00002233415,0.0002138379,0.005426083],"genre_scores_gemma":[0.972694,0.000004615933,0.02671732,0.00003667946,0.00007638059,0.000007386324,0.00000372378,0.000003674961,0.0004562317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9078171,"threshold_uncertainty_score":0.6429968,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2412732296","doi":"10.1287/mksc.2015.0975","title":"Social Responsibility and Product Innovation","year":2016,"lang":"en","type":"article","venue":"Marketing Science","topic":"Environmental Sustainability in Business","field":"Business, Management and Accounting","cited_by":130,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Incentive; Monopoly; Competition (biology); Product (mathematics); Economics; Value (mathematics); Microeconomics; Social responsibility; Consumption (sociology); Business; Industrial organization; Public economics; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.01390914653700447,"gpt":0.2490210145032563,"spread":0.2351118679662518,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006378925,0.00008246173,0.00007116109,0.0002178087,0.0005173153,0.0001968562,0.0002120851,0.00001805988,0.00006394553],"category_scores_gemma":[0.006696769,0.0000586962,0.000009695238,0.001563838,0.001012087,0.001631187,0.0003936444,0.00004058894,0.00002505306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00011959,"about_ca_system_score_gemma":0.00003268062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002958622,"about_ca_topic_score_gemma":0.000003490371,"domain_scores_codex":[0.998807,0.00002164676,0.0001706316,0.0004166822,0.000328346,0.0002556549],"domain_scores_gemma":[0.9994052,0.00009769679,0.0001137573,0.0001892157,0.0001889397,0.000005199829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001229682,0.00004123752,0.7753373,0.0001182152,0.000001113541,0.000001511961,0.00003793256,5.100906e-7,0.08159919,0.01449224,0.0004686605,0.1277791],"study_design_scores_gemma":[0.0001272609,0.00000145147,0.9889197,0.00001743633,0.000002541266,8.000666e-7,0.00004171898,0.00004194734,0.0004240865,0.003784033,0.006534052,0.0001050007],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866836,0.000004921626,0.00006917965,0.008002734,0.000100994,0.0001630303,3.069289e-7,0.00006688099,0.004908341],"genre_scores_gemma":[0.9988222,4.753701e-7,0.0001931696,0.0003829212,0.0002868615,0.000007365968,3.948518e-7,0.000006095657,0.000300536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2135823,"threshold_uncertainty_score":0.8017142,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2118339517","doi":"10.1287/mksc.1090.0545","title":"Durable Products with Multiple Used Goods Markets: Product Upgrade and Retail Pricing Implications","year":2009,"lang":"en","type":"article","venue":"Marketing Science","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":130,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Business; Commerce; Product (mathematics); Durable good; Context (archaeology); Profit (economics); Product market; Industrial organization; Database transaction; Economics; Microeconomics; Incentive","retraction":null,"screen_n_in":null,"score":{"opus":0.01608255174741179,"gpt":0.2012334903361774,"spread":0.1851509385887656,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001990366,0.0001519903,0.0001425062,0.0001888227,0.0005948959,0.001671901,0.0003249088,0.00001821353,0.00001111407],"category_scores_gemma":[0.001255973,0.0001212966,0.00001596129,0.001063947,0.000210341,0.005834396,0.0001151893,0.00009012662,0.00002065707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004009993,"about_ca_system_score_gemma":0.00005706111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003870023,"about_ca_topic_score_gemma":0.00002314322,"domain_scores_codex":[0.9985837,0.000002054749,0.0002091857,0.0005829511,0.0001782854,0.0004437652],"domain_scores_gemma":[0.9992552,0.00006035291,0.0001838737,0.0003539766,0.0001202625,0.0000262871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003732973,0.0003045088,0.7637687,0.0004828416,0.00002297594,0.000008884986,0.0002436574,0.000307186,0.04428286,0.01871416,0.003295223,0.1681958],"study_design_scores_gemma":[0.0003290648,0.00001565638,0.985263,0.00009625564,0.00001387498,0.00001459807,0.0002654702,0.00497052,0.0004625909,0.001259621,0.006974955,0.0003343968],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9381293,0.00003136244,0.0000251286,0.002571687,0.00007245525,0.0003041538,6.629576e-7,0.0001175543,0.05874771],"genre_scores_gemma":[0.9971229,0.0000049217,0.001795184,0.0005110737,0.000191883,0.000008441003,0.000004126176,0.00001168491,0.0003498034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2214943,"threshold_uncertainty_score":0.9993644,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2088759092","doi":"10.1287/mksc.1030.0053","title":"A General Theory of Pass-Through in Channels with Category Management and Retail Competition","year":2005,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":129,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Complementarity (molecular biology); Competition (biology); Brand management; Store brand; Business; Marketing; Sign (mathematics); Microeconomics; Advertising; Economics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01742455449122676,"gpt":0.2260320368084544,"spread":0.2086074823172276,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003105405,0.000112577,0.0001311421,0.0002810998,0.0001656251,0.0001556893,0.0002147288,0.00001975268,0.0001359356],"category_scores_gemma":[0.00006422944,0.00009675093,0.00001661916,0.0008157931,0.0003228085,0.000966892,0.0002015244,0.000081659,0.000005669031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002658257,"about_ca_system_score_gemma":0.00001556439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001830584,"about_ca_topic_score_gemma":0.00009664377,"domain_scores_codex":[0.9988783,0.00003397624,0.0002015964,0.0003114932,0.0002969531,0.0002777092],"domain_scores_gemma":[0.9995525,0.00007263452,0.0001264506,0.000168114,0.00007027714,0.00001002414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004623845,0.0001409673,0.6040791,0.0005457222,0.00001338594,0.00003182407,0.0005428817,0.0003070969,0.002893059,0.06486208,0.0001003788,0.3260211],"study_design_scores_gemma":[0.0006993021,0.000009796343,0.9855961,0.0002867786,0.0000415227,0.000006389215,0.0006144697,0.005094606,0.0001690482,0.001174113,0.006031223,0.0002766755],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9380262,0.0001167435,0.0003610131,0.0002833794,0.00008045792,0.0001669541,3.246761e-7,0.00003307205,0.06093178],"genre_scores_gemma":[0.9974642,0.00002160616,0.001667848,0.0002935847,0.00009189226,0.00001234472,0.000001549451,0.000008709239,0.0004382843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.381517,"threshold_uncertainty_score":0.3945388,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2046774624","doi":"10.1287/mksc.1070.0323","title":"<b>Research Note</b>—Does Demand Fall When Customers Perceive That Prices Are Unfair? The Case of Premium Pricing for Large Sizes","year":2008,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":125,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Order (exchange); Price premium; Economics; Price discrimination; Business; Pricing strategies; Clothing; Microeconomics; Advertising; Econometrics; Marketing; Willingness to pay","retraction":null,"screen_n_in":null,"score":{"opus":0.04182797654971324,"gpt":0.30675620870501,"spread":0.2649282321552968,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.01355349,0.0002174891,0.000271291,0.0005271499,0.002855769,0.0004150222,0.0009373722,0.00006373578,0.00007592594],"category_scores_gemma":[0.002778974,0.0001400561,0.0001133311,0.001398195,0.0008123615,0.001280747,0.0006805404,0.0003057249,0.000009555147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006588134,"about_ca_system_score_gemma":0.0001253828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001652735,"about_ca_topic_score_gemma":0.001131541,"domain_scores_codex":[0.9972633,0.0001115668,0.0003402659,0.000611383,0.0007784364,0.0008951031],"domain_scores_gemma":[0.9961706,0.002236052,0.0003607162,0.0004671668,0.0007292355,0.00003624156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003217448,0.0001700418,0.960188,0.001069471,0.00002394255,0.0002445205,0.005072339,0.0000581849,0.006256885,0.000688108,0.002091257,0.02381551],"study_design_scores_gemma":[0.001267123,0.00003080488,0.9223869,0.0007164911,0.0001821394,0.0002594379,0.03153564,0.02566823,0.001368929,0.0003938481,0.01535303,0.0008374149],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874666,0.0001698562,0.0003640002,0.0005896214,0.0003539137,0.0007268841,0.000007307672,0.00007954173,0.01024222],"genre_scores_gemma":[0.9985117,0.00002620134,0.0005725909,0.0001510413,0.0002399546,0.00005052541,0.000001690414,0.00002539435,0.0004209303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03780109,"threshold_uncertainty_score":0.9984424,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2003050740","doi":"10.1287/mksc.1120.0745","title":"Advertising Effects in Presidential Elections","year":2012,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":121,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Stanford Graduate School of Business; University of Toronto; Yale University","keywords":"Endogeneity; Advertising; Instrumental variable; Context (archaeology); Presidential system; Victory; Economics; Presidential election; Margin (machine learning); General election; Econometrics; Business; Political science; Computer science; Politics; Law","retraction":null,"screen_n_in":null,"score":{"opus":0.009452537077414907,"gpt":0.2458884152945079,"spread":0.2364358782170929,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003864778,0.0001057207,0.0000999699,0.0005078434,0.0004375576,0.0003334475,0.0002761316,0.00002670382,0.0001369423],"category_scores_gemma":[0.001538586,0.0001068581,0.00003366486,0.001732835,0.0001242575,0.00248691,0.0002340548,0.0001398837,0.0000722362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005144059,"about_ca_system_score_gemma":0.00003149247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000661905,"about_ca_topic_score_gemma":0.0001277612,"domain_scores_codex":[0.9986237,0.00003202951,0.0001754227,0.0002380988,0.0003291795,0.0006015933],"domain_scores_gemma":[0.9994631,0.0002095798,0.00007894883,0.0001687114,0.0000579158,0.00002170104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001759637,0.00003617246,0.9534729,0.00005766609,9.567045e-7,0.000002637621,0.00004672509,0.000006292034,0.01184219,0.0005290119,0.0001689677,0.03381892],"study_design_scores_gemma":[0.0001539511,0.00000114794,0.9962395,0.00009026097,0.00001565697,0.000003541924,0.00004464923,0.001156264,0.000257383,0.0001076921,0.001781782,0.0001482174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9496209,0.0001262623,0.0002880638,0.00007398042,0.001039099,0.0001485483,6.968704e-8,0.00009630011,0.04860677],"genre_scores_gemma":[0.9989081,0.000001447756,0.0002885704,0.0001894566,0.0004227079,0.0000127008,5.23203e-7,0.00001046723,0.000166024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0492872,"threshold_uncertainty_score":0.4357545,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2090012050","doi":"10.1287/mksc.1110.0693","title":"Demand Dynamics in the Seasonal Goods Industry: An Empirical Analysis","year":2012,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":115,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Purchasing; Revenue; Product (mathematics); Context (archaeology); Economics; Business; Consumption (sociology); Stockout; Microeconomics; Marketing; Commerce","retraction":null,"screen_n_in":null,"score":{"opus":0.03147280020498721,"gpt":0.3092954863369617,"spread":0.2778226861319745,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01347482,0.0001331028,0.0001496564,0.0005109276,0.0004672741,0.000624598,0.0007236068,0.00007590067,0.0002121408],"category_scores_gemma":[0.0007539012,0.0000979437,0.00006323519,0.005432907,0.00023609,0.001771864,0.0002315152,0.0003795977,0.00001384702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007870705,"about_ca_system_score_gemma":0.00004202426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003901315,"about_ca_topic_score_gemma":0.0006723857,"domain_scores_codex":[0.998198,0.0001183245,0.0002061057,0.0003019335,0.0005924459,0.0005832448],"domain_scores_gemma":[0.9992008,0.0002638008,0.0001092457,0.000329823,0.00006246076,0.00003392782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000131536,0.00006179503,0.9870521,0.000008605122,0.000005505022,0.000002420986,0.0001185834,0.00001960062,0.00002304999,0.000356727,0.00008240977,0.012256],"study_design_scores_gemma":[0.00007823852,0.000001619729,0.9317291,0.00001036857,0.0001345254,0.000002474727,0.001055517,0.06560439,0.000001106542,0.00003083862,0.001209824,0.0001419325],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9694739,0.00003508234,0.0001343442,0.0006973821,0.0001700452,0.0000916402,9.776577e-7,0.00004005196,0.0293566],"genre_scores_gemma":[0.9984622,8.855999e-7,0.0001800428,0.0009920829,0.0002893053,0.00000812544,0.000007358254,0.000007137509,0.0000528589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06558479,"threshold_uncertainty_score":0.6023013,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1994575315","doi":"10.1287/mksc.20.2.194.10192","title":"Evaluating Promotions in Shopping Environments: Decomposing Sales Response into Attraction, Conversion, and Spending Effects","year":2001,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":111,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Western University","funders":"","keywords":"Marketing; Advertising; Business; Variety (cybernetics); Casual; Product (mathematics); Liberian dollar; Promotion (chess); Clothing; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.03139095173404811,"gpt":0.3117981917724357,"spread":0.2804072400383876,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01134031,0.0001798824,0.0001684083,0.0007467857,0.001114495,0.0005689572,0.000266142,0.00004193776,0.00008115087],"category_scores_gemma":[0.003473903,0.0001909162,0.00003180478,0.001262059,0.0003038167,0.002010332,0.0003684814,0.000197169,0.00003465057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001648118,"about_ca_system_score_gemma":0.00003863186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002095903,"about_ca_topic_score_gemma":0.00005561868,"domain_scores_codex":[0.9980122,0.0001686758,0.0003270698,0.0005632613,0.00047087,0.0004578805],"domain_scores_gemma":[0.9984822,0.001028064,0.0001951538,0.0002164096,0.00004540343,0.00003279334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001991758,0.00003700305,0.7890731,0.00009014184,0.000002296843,0.0000255743,0.000143214,0.00009473615,0.1768076,0.00002135818,0.000005827628,0.03349992],"study_design_scores_gemma":[0.0004454033,0.00001016989,0.9704924,0.0004735031,0.00002783226,0.00002180884,0.0003915964,0.02672544,0.0002366965,0.00006296132,0.0008712033,0.0002410178],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973345,0.0001014005,0.0004834718,0.0003225264,0.000336208,0.000309813,1.145671e-7,0.00006951243,0.001042461],"genre_scores_gemma":[0.9982384,0.00001612341,0.001420328,0.000116301,0.00009185815,0.00001509104,0.000002099801,0.00001677622,0.00008295775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1814192,"threshold_uncertainty_score":0.8571909,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2145079868","doi":"10.1287/mksc.1080.0376","title":"Measuring Brand Value in an Equilibrium Framework","year":2008,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":111,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"General Mills","keywords":"Counterfactual thinking; Competitor analysis; Value (mathematics); Brand equity; Profit (economics); Econometrics; Marketing; Key (lock); Brand management; Advertising; Microeconomics; Economics; Business; Computer science; Mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.04974654886188077,"gpt":0.2562864915175885,"spread":0.2065399426557077,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004917926,0.0001578436,0.0001673129,0.0005102978,0.000502961,0.0004218103,0.0006668791,0.00005089747,0.0001630499],"category_scores_gemma":[0.001822999,0.0001587846,0.00004090175,0.001951636,0.0003384238,0.002430012,0.0003340757,0.0002511489,0.00004834053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004441589,"about_ca_system_score_gemma":0.00007694734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004766639,"about_ca_topic_score_gemma":0.00004947753,"domain_scores_codex":[0.9980077,0.00004705504,0.0002714612,0.0005137846,0.0005891315,0.0005708344],"domain_scores_gemma":[0.9991401,0.0002310014,0.0001090468,0.0003669029,0.0001217298,0.00003120416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005767796,0.00004223653,0.9789051,0.00004149206,8.503603e-7,0.00003923635,0.0001481177,0.0001277561,0.008712579,0.000376579,0.00003716089,0.01151124],"study_design_scores_gemma":[0.0002097707,0.000003416456,0.9873048,0.0001660873,0.00000783418,0.00001058671,0.00009291599,0.01059401,0.0001655696,0.0003972724,0.0007768229,0.0002709195],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9699623,0.00006413837,0.0001219381,0.0001542227,0.0004564016,0.0001283788,2.124595e-7,0.000134057,0.02897835],"genre_scores_gemma":[0.9981278,0.000003677878,0.001087484,0.0003754408,0.0003029926,0.000006925673,8.218483e-7,0.00001752629,0.00007737405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02890098,"threshold_uncertainty_score":0.6475049,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3184694980","doi":"10.1287/mksc.2021.1295","title":"Frontiers: Can an Artificial Intelligence Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb","year":2021,"lang":"en","type":"article","venue":"Marketing Science","topic":"Sharing Economy and Platforms","field":"Business, Management and Accounting","cited_by":109,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Revenue; Context (archaeology); Algorithm; Population; Computer science; Economics; Machine learning; Finance; Geography; Sociology","retraction":null,"screen_n_in":null,"score":{"opus":0.02925166095697394,"gpt":0.2638301363844498,"spread":0.2345784754274759,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00675215,0.0001256104,0.000250367,0.0004298019,0.0002871802,0.0006553701,0.0007785434,0.00004196393,0.000167654],"category_scores_gemma":[0.0004892914,0.0001064027,0.00008113702,0.001542174,0.0002997866,0.001868289,0.0001384824,0.0001345511,0.00001319461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005761755,"about_ca_system_score_gemma":0.0001345159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002673575,"about_ca_topic_score_gemma":0.009131729,"domain_scores_codex":[0.9984548,0.00006419032,0.0004591336,0.0004718691,0.0002227235,0.0003272648],"domain_scores_gemma":[0.9990608,0.0001274259,0.0002573909,0.0004153186,0.0001166541,0.00002237983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001200461,0.0002711354,0.345099,0.00007686725,0.00007464215,0.00004225812,0.004879712,0.003645539,0.000559494,0.02119371,0.00007135699,0.6239663],"study_design_scores_gemma":[0.0001274384,0.00001804551,0.1467539,0.00004235368,0.0001203659,0.000002799438,0.03253579,0.8071972,0.002085875,0.009895857,0.0007969876,0.0004233982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953899,0.00002421827,0.002037605,0.0003796726,0.0003734694,0.00009390443,0.00001095068,0.00002341689,0.001666829],"genre_scores_gemma":[0.9976095,0.000002854545,0.001227297,0.0007838303,0.0003211576,0.000006423047,0.00003227169,0.000005743631,0.00001092564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8035516,"threshold_uncertainty_score":0.6319749,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1981842168","doi":"10.1287/mksc.1070.0310","title":"Informing, Transforming, and Persuading: Disentangling the Multiple Effects of Advertising on Brand Choice Decisions","year":2008,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":107,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia; University of Toronto","funders":"","keywords":"Transformative learning; Ambiguity; Credibility; Advertising; Marketing; Quality (philosophy); Consumption (sociology); Product (mathematics); Economics; Psychology; Business; Computer science; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.01751104169903839,"gpt":0.2426830432721786,"spread":0.2251720015731402,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001859335,0.0001642831,0.0001737523,0.0003115854,0.001506101,0.0001851454,0.0004006985,0.00003181286,0.00001600847],"category_scores_gemma":[0.005683554,0.0001188413,0.00006691521,0.0009251396,0.0005546854,0.001013131,0.0001774278,0.0001650163,0.000003951291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000223357,"about_ca_system_score_gemma":0.0000408951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001764616,"about_ca_topic_score_gemma":0.00004983499,"domain_scores_codex":[0.9984893,0.00002126611,0.0002791279,0.0003143531,0.0005237578,0.0003721649],"domain_scores_gemma":[0.9968688,0.002590159,0.0001629877,0.0002455642,0.0001040976,0.00002834291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001032861,0.00003919878,0.8227169,0.0001231012,0.000006231745,0.00001458809,0.0007788792,0.00002395443,0.008562828,0.0001673311,0.00005716929,0.1674066],"study_design_scores_gemma":[0.001029638,0.00001854295,0.9749498,0.0007283182,0.00007402403,0.00002894292,0.0004106274,0.01394716,0.002525553,0.0000385567,0.005916447,0.0003324038],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894261,0.0001802721,0.0001472395,0.000109585,0.0003116012,0.0002814188,4.541937e-7,0.00005283579,0.009490539],"genre_scores_gemma":[0.9993502,0.00004793707,0.0001484,0.0002369904,0.0001167303,0.000007991252,6.842608e-7,0.00001297849,0.00007808257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1670742,"threshold_uncertainty_score":0.9997938,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2157434061","doi":"10.1287/mksc.1090.0513","title":"Estimating the Value of Brand Alliances in Professional Team Sports","year":2009,"lang":"en","type":"article","venue":"Marketing Science","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":105,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; Simon Fraser University","funders":"","keywords":"Brand equity; Basketball; Business; Marketing; Value (mathematics); Advertising; Matching (statistics); Brand management; Revenue; Sports marketing; Salary; Economics; Marketing management; Statistics; Finance; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.0143187553134311,"gpt":0.2480565901737759,"spread":0.2337378348603448,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005984799,0.00006985797,0.0001640118,0.0001332125,0.0001877129,0.00004772065,0.0003693062,0.00002285314,0.00009409412],"category_scores_gemma":[0.0003967487,0.00005380033,0.0000323645,0.0006293735,0.0001977019,0.0002177173,0.00003744602,0.0001083168,0.000005148379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002810812,"about_ca_system_score_gemma":0.00005390991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005452751,"about_ca_topic_score_gemma":0.000005125811,"domain_scores_codex":[0.9989498,0.000008393114,0.0004383874,0.0002532798,0.0001117704,0.0002383731],"domain_scores_gemma":[0.9993503,0.00007132298,0.0003175466,0.0002020518,0.00002709413,0.00003169347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001830171,0.00005708378,0.9558586,0.0000208723,0.000001494689,0.000001846474,0.0006103899,0.0170634,0.00007649285,0.01832066,0.000232253,0.007738606],"study_design_scores_gemma":[0.00007327639,0.00001021798,0.7192461,0.0000828709,5.265758e-7,0.000001430865,0.00003561916,0.2762574,0.00003598149,0.003369346,0.0008229973,0.00006420095],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721463,0.0003049012,0.0001719774,0.0005789633,0.0004862024,0.00008797271,0.000002773046,0.000006877036,0.02621399],"genre_scores_gemma":[0.9976671,0.00002351784,0.001502377,0.0001883816,0.00004939512,0.000002005098,4.327734e-7,0.000002866456,0.0005638634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.259194,"threshold_uncertainty_score":0.2193914,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2115482408","doi":"10.1287/mksc.1070.0285","title":"Research Note—Channel Structure with Knowledge Spillovers","year":2008,"lang":"en","type":"article","venue":"Marketing Science","topic":"Merger and Competition Analysis","field":"Economics, Econometrics and Finance","cited_by":99,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Competitor analysis; Incentive; Industrial organization; Competition (biology); Business; Process (computing); Channel (broadcasting); Investment (military); Organizational structure; Marketing; Microeconomics; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.05125151237060682,"gpt":0.2822605861998763,"spread":0.2310090738292695,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003499702,0.00009028443,0.0001765576,0.00059947,0.0008126628,0.00008473529,0.0004830336,0.00003463398,0.001139461],"category_scores_gemma":[0.0004906924,0.00008508335,0.00004028908,0.002451642,0.0007121636,0.0002179432,0.0001059446,0.0002102969,0.0003941003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001154976,"about_ca_system_score_gemma":0.0001068788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009120172,"about_ca_topic_score_gemma":0.00004073071,"domain_scores_codex":[0.9986123,0.00004832022,0.000234314,0.0005121118,0.0001589608,0.0004339735],"domain_scores_gemma":[0.9991564,0.000117763,0.00009159676,0.00034728,0.0001612133,0.0001257053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005142429,0.0006939583,0.5805047,0.000272498,0.0001504355,0.0001726657,0.01493207,0.003491709,0.004732374,0.3543605,0.0284893,0.01168555],"study_design_scores_gemma":[0.001226428,0.0002388905,0.8460385,0.0001349853,0.000009598823,0.0001139304,0.001491049,0.04342686,0.001852747,0.01144235,0.09277613,0.001248567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6431282,0.0003508102,0.001065549,0.0003032558,0.0002163878,0.00007454585,0.00001594548,0.00003400221,0.3548113],"genre_scores_gemma":[0.9950863,0.00005933061,0.0009011781,0.00006190623,0.00007040587,0.000003887832,0.000001531383,0.000008672379,0.003806771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3519581,"threshold_uncertainty_score":0.9997736,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2097321609","doi":"10.1287/mksc.22.4.442.24910","title":"Enriching Scanner Panel Models with Choice Experiments","year":2003,"lang":"en","type":"article","venue":"Marketing Science","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":98,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Pooling; Scanner; Panel data; Computer science; Data set; Choice set; Data mining; Econometrics; Artificial intelligence; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.1394103842131127,"gpt":0.2298683275328421,"spread":0.09045794331972937,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002660088,0.0001018175,0.0001335846,0.0001153135,0.0003074234,0.000109561,0.0002257934,0.00002607935,0.000302037],"category_scores_gemma":[0.0002153269,0.0001049337,0.000024193,0.0002333012,0.0001794786,0.0007135672,0.00004260445,0.00007129241,0.0001700055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001895941,"about_ca_system_score_gemma":0.00002310784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008473248,"about_ca_topic_score_gemma":0.00000360104,"domain_scores_codex":[0.9988933,0.00002298287,0.0002501122,0.0004593196,0.00006280024,0.0003114602],"domain_scores_gemma":[0.9994501,0.00005799717,0.0001666562,0.0002362004,0.00000849167,0.00008058132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001405061,0.00009068545,0.8640499,0.00001265317,0.00001345423,0.000001272732,0.0009078379,0.01314295,0.001100826,0.1193075,0.0001223327,0.001236595],"study_design_scores_gemma":[0.001159961,0.000081713,0.9036781,0.00005360409,0.000006154273,0.0000157804,0.0007168697,0.07302973,0.002058759,0.01185927,0.006509605,0.000830506],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8221236,0.0001842085,0.004223268,0.00004399927,0.0001451156,0.00008609057,0.000002577705,0.00001896551,0.1731722],"genre_scores_gemma":[0.9922872,0.00001665126,0.00588403,0.0001721263,0.0000193966,0.00001533028,9.790123e-7,0.00001225779,0.001592098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1715801,"threshold_uncertainty_score":0.4279071,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2153734407","doi":"10.1287/mksc.1060.0214","title":"Investigating Consumers’ Purchase Incidence and Brand Choice Decisions Across Multiple Product Categories: A Theoretical and Empirical Analysis","year":2007,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":96,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Portfolio; Product (mathematics); Flexibility (engineering); Econometrics; Product category; Marketing; Economics; Business; Mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.02901781902836841,"gpt":0.323415535931023,"spread":0.2943977169026545,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.01366995,0.000244596,0.0003167739,0.0005164839,0.001588596,0.001165849,0.000408424,0.00005750184,0.00005611727],"category_scores_gemma":[0.02929524,0.0002142965,0.00005926051,0.003877818,0.003238467,0.001177468,0.0008769843,0.0002869774,0.000005501796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003142727,"about_ca_system_score_gemma":0.00007368321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009541771,"about_ca_topic_score_gemma":0.001119041,"domain_scores_codex":[0.9971529,0.00005648455,0.0004613562,0.0009002485,0.0006482662,0.0007807865],"domain_scores_gemma":[0.9955112,0.003452315,0.0002152013,0.0003829073,0.0003131434,0.0001251731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004155546,0.00002000241,0.9432567,0.00002976567,0.00001499057,0.00001019201,0.000515799,0.000003249736,0.002673412,0.0002640463,0.00001617339,0.05315417],"study_design_scores_gemma":[0.0003693359,0.00000465927,0.9860335,0.00006594354,0.0001870822,0.00001425524,0.0009431395,0.01083696,0.0001318246,0.0003336046,0.0007762959,0.0003034108],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961578,0.0002130061,0.001334621,0.0005567495,0.0001362236,0.0002400691,0.000002687617,0.00009757145,0.001261246],"genre_scores_gemma":[0.9975626,0.00001338481,0.001649487,0.0006038885,0.0001180128,0.000007912643,0.000003319885,0.00001472062,0.00002661079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05285076,"threshold_uncertainty_score":0.999871,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2112301042","doi":"10.1287/mksc.1100.0564","title":"An Empirical Analysis of Assortment Similarities Across U.S. Supermarkets","year":2010,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":84,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National University of Singapore; McGill University; Singapore Management University; University of Washington","keywords":"Business; Extant taxon; Context (archaeology); Order (exchange); Distribution (mathematics); Marketing; Advertising; Pairwise comparison; Industrial organization; Mathematics; Geography; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.02174921574202841,"gpt":0.322229933162735,"spread":0.3004807174207065,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008266029,0.0001738285,0.000301696,0.0006788596,0.0005889196,0.0006159492,0.0008224528,0.0000637275,0.000842129],"category_scores_gemma":[0.00119747,0.0001595054,0.0001425722,0.003644876,0.0006488878,0.001479277,0.0003443006,0.0002430567,0.000008294538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000194273,"about_ca_system_score_gemma":0.00006309214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004318263,"about_ca_topic_score_gemma":0.0009096099,"domain_scores_codex":[0.9977927,0.00003904975,0.0003793756,0.0005151306,0.0007289064,0.0005448032],"domain_scores_gemma":[0.9985298,0.000284738,0.0001992191,0.0005855433,0.0003599366,0.00004078676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003813786,0.00008104882,0.9498956,0.00002861875,0.00002730356,0.000004005089,0.0001310482,0.00001956111,0.03094096,0.00008149341,0.00008476945,0.01866741],"study_design_scores_gemma":[0.0001200293,0.000004204368,0.9762565,0.00001203146,0.0002582737,0.000001016711,0.0003388519,0.02019057,0.0002680955,0.00002687865,0.002319222,0.0002042712],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868504,0.00001186193,0.00004461077,0.0001995497,0.0004777508,0.0001030849,0.000008595717,0.00009326638,0.0122109],"genre_scores_gemma":[0.9988496,0.000002031544,0.0004898531,0.0004280951,0.0001397723,0.000007769268,0.00001266085,0.00001191823,0.00005832858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03067286,"threshold_uncertainty_score":0.9220722,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3123976429","doi":"10.1287/mksc.2019.1150","title":"What Do News Aggregators Do? Evidence from Google News in Spain and Germany","year":2019,"lang":"en","type":"article","venue":"Marketing Science","topic":"Media Influence and Politics","field":"Social Sciences","cited_by":84,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"News aggregator; Advertising; Business; Computer science; Marketing; Internet privacy; World Wide Web","retraction":null,"screen_n_in":null,"score":{"opus":0.02237600695141442,"gpt":0.3165545822482985,"spread":0.2941785752968841,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007544915,0.000135587,0.0001919252,0.0001750831,0.0003955867,0.001052673,0.0007771464,0.00009064112,0.0004090604],"category_scores_gemma":[0.006205775,0.0001273086,0.00003310013,0.001001212,0.001090717,0.002493267,0.0001847582,0.0002053627,0.0001839074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001600493,"about_ca_system_score_gemma":0.0005781899,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0109955,"about_ca_topic_score_gemma":0.002964418,"domain_scores_codex":[0.9970194,0.0005137697,0.0002878468,0.000581225,0.0008590588,0.0007387709],"domain_scores_gemma":[0.9969139,0.002169576,0.0001475302,0.0003784933,0.00007996368,0.000310522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001571173,0.00001117349,0.9234869,0.00001689365,0.000001270698,0.000008914682,0.02124842,0.000009066674,0.001574928,0.001177423,0.0002250527,0.05222419],"study_design_scores_gemma":[0.0006266065,0.00008479645,0.7942775,0.005467772,0.00001738326,0.000004000909,0.1050062,0.0009981705,0.000643881,0.005293484,0.0864958,0.001084355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9851431,0.001941325,0.000003777208,0.002326473,0.001323889,0.0002868637,0.000001632848,0.0000363871,0.008936572],"genre_scores_gemma":[0.9940122,0.003337758,0.000633127,0.0008942261,0.0002269267,0.000008814826,3.078173e-7,0.000007421051,0.0008791824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1292094,"threshold_uncertainty_score":0.9999843,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2911554803","doi":"10.1287/mksc.2018.1126","title":"Sensor Data and Behavioral Tracking: Does Usage-Based Auto Insurance Benefit Drivers?","year":2019,"lang":"en","type":"article","venue":"Marketing Science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Tracking (education); Computer science; Business; Actuarial science; Econometrics; Marketing; Economics; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.0222233016187394,"gpt":0.2686624013149462,"spread":0.2464390996962068,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008998435,0.00008402407,0.00007932416,0.0001006447,0.0001902277,0.00008319875,0.0003307048,0.00002691869,0.0000720208],"category_scores_gemma":[0.0000667963,0.00007539129,0.00001055277,0.000479987,0.0001640317,0.000453193,0.0000362415,0.00009558538,0.000008173776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002570353,"about_ca_system_score_gemma":0.00003645202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001500797,"about_ca_topic_score_gemma":0.00005355162,"domain_scores_codex":[0.999118,0.000009764119,0.0001534966,0.0002971284,0.0002224288,0.0001991727],"domain_scores_gemma":[0.9993532,0.0000820928,0.00002621029,0.0004171251,0.00006848886,0.00005290573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00000871259,0.0000284315,0.9074368,0.00008042788,0.000002892728,0.000002536166,0.0004990318,0.005272797,0.07128233,0.0001519,0.00002702343,0.01520714],"study_design_scores_gemma":[0.0001813366,0.000007133112,0.9406086,0.00003801334,0.000004366505,9.364934e-7,0.0001355209,0.05574012,0.001532247,0.000006014611,0.001620912,0.0001247913],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977365,0.00001060879,0.0007455592,0.00009225125,0.0002952076,0.0001303674,0.00009034639,0.0001911242,0.0007080382],"genre_scores_gemma":[0.9958715,0.000003470538,0.003937071,0.00004454386,0.00001046519,0.000003032189,0.00001854418,0.00000812462,0.000103178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06975009,"threshold_uncertainty_score":0.3074368,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2128125016","doi":"10.1287/mksc.1030.0042","title":"Is Having More Channels Really Better? A Model of Competition Among Commercial Television Broadcasters","year":2004,"lang":"en","type":"article","venue":"Marketing Science","topic":"Merger and Competition Analysis","field":"Economics, Econometrics and Finance","cited_by":73,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Competitor analysis; Competition (biology); Monopoly; Duopoly; Quality (philosophy); Broadcasting (networking); Business; Advertising; Television industry; Marketing; Telecommunications; Industrial organization; Economics; Microeconomics; Computer science; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.02953738216073945,"gpt":0.2417193884060499,"spread":0.2121820062453104,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002134001,0.0001210168,0.0002840787,0.0004441675,0.0002807024,0.0001079486,0.0004140432,0.00004390319,0.0002306392],"category_scores_gemma":[0.0001860021,0.0001403037,0.0001240909,0.0007786229,0.0003562324,0.0003744218,0.0001171529,0.0001084283,0.00003732386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001034023,"about_ca_system_score_gemma":0.00003907098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002894075,"about_ca_topic_score_gemma":0.00001439846,"domain_scores_codex":[0.9985399,0.00002003,0.0005425104,0.0004510251,0.0001539313,0.0002925645],"domain_scores_gemma":[0.9991022,0.00003778863,0.0003589455,0.0003198398,0.00008518077,0.00009599026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001947552,0.0007142671,0.671239,0.0004785061,0.00009115818,0.00001354745,0.01360838,0.1349879,0.01951423,0.1327371,0.0006818236,0.02573938],"study_design_scores_gemma":[0.001109132,0.00008016168,0.4496064,0.0005151877,0.00002396001,0.000005104735,0.0006040471,0.5285257,0.003552516,0.01493627,0.0002903244,0.0007512415],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9556789,0.00004867576,0.02953852,0.001115532,0.0001650837,0.00008354484,0.00002907866,0.00002674232,0.01331395],"genre_scores_gemma":[0.995743,0.00003285607,0.003440312,0.0005898427,0.00004022634,0.000005281946,0.000004802839,0.000009922356,0.0001337218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3935378,"threshold_uncertainty_score":0.5721419,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2134280878","doi":"10.1287/mksc.1090.0546","title":"Limited Memory, Categorization, and Competition","year":2009,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":67,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Categorization; Recall; Competition (biology); Microeconomics; Economics; Business; Marketing; Psychology; Cognitive psychology; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01214105879903812,"gpt":0.2263389400687305,"spread":0.2141978812696924,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001948015,0.00009016587,0.00008045078,0.0002675917,0.0005139833,0.0005487078,0.0001886735,0.00002013291,0.0001135353],"category_scores_gemma":[0.0005568173,0.00008696115,0.00001516732,0.001010946,0.0001513364,0.001006151,0.00008318216,0.00006689793,0.00002161866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001451864,"about_ca_system_score_gemma":0.0000202618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008074149,"about_ca_topic_score_gemma":0.000012167,"domain_scores_codex":[0.9990901,0.00001330391,0.0001384166,0.0002728867,0.0002546551,0.0002306431],"domain_scores_gemma":[0.9995405,0.00006258943,0.00008522275,0.0001407882,0.0001556051,0.00001525969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00008581395,0.00008264129,0.2963922,0.00009161848,0.000002841758,0.00001285994,0.0001445418,0.00002450532,0.03950366,0.02608873,0.0006135825,0.636957],"study_design_scores_gemma":[0.0001728657,0.000004237614,0.9897228,0.00004107487,0.00001623274,0.000004534,0.00009413735,0.004456028,0.0001017524,0.0009215368,0.004298188,0.0001665634],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9141984,0.00005347157,0.0003165463,0.001281835,0.0002262078,0.0001081777,2.176192e-7,0.0001438802,0.08367126],"genre_scores_gemma":[0.9983953,0.000006948181,0.0002224971,0.001054696,0.0001598755,0.000001709363,0.000003706999,0.000004697172,0.0001505229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6933307,"threshold_uncertainty_score":0.5291202,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3046925189","doi":"10.1287/mksc.2020.1231","title":"Profiting from the Decoy Effect: A Case Study of an Online Diamond Retailer","year":2020,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Decoy; Diamond; Marketing; Business; Industrial organization; Microeconomics; Advertising; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.04087028983882487,"gpt":0.2734915420644944,"spread":0.2326212522256696,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004008823,0.0001611196,0.0002033366,0.00008562586,0.0006406512,0.000413962,0.0006669035,0.00002388333,0.0001321684],"category_scores_gemma":[0.002678041,0.0001126674,0.00004203317,0.001377671,0.0001821352,0.0009064394,0.0005405686,0.0002055878,0.000008267506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001190487,"about_ca_system_score_gemma":0.00003328005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005173998,"about_ca_topic_score_gemma":0.0009894767,"domain_scores_codex":[0.9982555,0.0001326913,0.0003208304,0.0004974875,0.0004895317,0.0003039407],"domain_scores_gemma":[0.9984175,0.0007816028,0.0002554629,0.0003621712,0.000150684,0.00003260217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009427224,0.0001100821,0.9089817,0.00005355104,0.000006613743,0.0002802273,0.00123951,0.00001203034,0.004105504,0.000002902888,0.00004847101,0.0850651],"study_design_scores_gemma":[0.0008241425,0.00007716198,0.9502288,0.00009290721,0.0001681814,0.00002536118,0.01513973,0.032574,0.0001880049,0.000008107597,0.0003857089,0.0002878883],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976838,0.00003295279,0.000009265174,0.0003245582,0.0001566027,0.0004976495,0.000003669555,0.00008690486,0.001204636],"genre_scores_gemma":[0.9988833,4.159744e-7,0.0001710305,0.0005227514,0.000382835,0.00001250264,0.000003725396,0.0000154457,0.000007979571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08477722,"threshold_uncertainty_score":0.7821572,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2141013540","doi":"10.1287/mksc.1050.0149","title":"The Lead-Lag Puzzle of Demand and Distribution: A Graphical Method Applied to Movies","year":2005,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Lag; Rendering (computer graphics); Revenue; Computer science; Box office; Econometrics; Lead–lag compensator; Causality (physics); Distribution (mathematics); Exhibition; Film industry; Econometric model; Economics; Advertising; Artificial intelligence; Mathematics; Business; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01172271707718292,"gpt":0.2611785315225819,"spread":0.249455814445399,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006481665,0.0001022389,0.0001263561,0.0001122712,0.0008989437,0.0003704131,0.0003551442,0.0000236142,0.00002322462],"category_scores_gemma":[0.0009484144,0.000073984,0.00003029367,0.001104118,0.0003767541,0.0003316505,0.0003623744,0.00009243548,0.000007850957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001300382,"about_ca_system_score_gemma":0.00001837996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000542717,"about_ca_topic_score_gemma":0.00007603691,"domain_scores_codex":[0.9988225,0.00002740223,0.0002166871,0.0002873261,0.0003424345,0.0003036796],"domain_scores_gemma":[0.9990885,0.000458626,0.0001029478,0.0002101983,0.0001178622,0.00002183026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002279544,0.00004512505,0.1068954,0.0001119704,0.00000848391,0.00000157086,0.0001526446,0.00004946101,0.03025301,0.01655825,0.001375787,0.8443203],"study_design_scores_gemma":[0.0003407538,0.00000674819,0.8908553,0.00008513279,0.00006430495,0.000006189792,0.0005784007,0.00559549,0.001755806,0.0006222277,0.09975395,0.0003357551],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671587,0.0002145134,0.005252142,0.003957508,0.0001617261,0.0002894674,0.00000236038,0.00006775351,0.02289584],"genre_scores_gemma":[0.9970321,0.00001134715,0.00245979,0.0002479978,0.0001281729,0.0000137278,0.000001068487,0.000005472623,0.0001003318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8439845,"threshold_uncertainty_score":0.6914039,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3091741951","doi":"10.1287/mksc.2020.1244","title":"Price Fairness and Strategic Obfuscation","year":2020,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Obfuscation; Business; Microeconomics; Industrial organization; Economics; Computer science; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.03396399956273907,"gpt":0.2407045736902185,"spread":0.2067405741274794,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00171144,0.0000952996,0.00008556816,0.0001066203,0.0003780742,0.0006633892,0.0002720003,0.00001930136,0.0001475278],"category_scores_gemma":[0.0005704198,0.00009030679,0.00001672357,0.001114513,0.000174632,0.0009560948,0.0002309812,0.00008800379,0.00004211978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000104365,"about_ca_system_score_gemma":0.00003788033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008146717,"about_ca_topic_score_gemma":0.000006957032,"domain_scores_codex":[0.9989828,0.00001363403,0.0001375599,0.0003476134,0.0002764272,0.0002419138],"domain_scores_gemma":[0.9995737,0.00008144937,0.00009536026,0.0001120066,0.0001106804,0.00002680235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001445404,0.00004431411,0.7802795,0.0005922297,0.000005725581,0.00001697402,0.000430772,0.00001780227,0.06875864,0.01833878,0.0004223342,0.1309484],"study_design_scores_gemma":[0.0003105274,0.000006820676,0.9585514,0.00006555473,0.00003421354,0.000004070327,0.0009554878,0.03278812,0.0001649208,0.0009752358,0.005766463,0.0003771564],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8989276,0.00005008113,0.0001142274,0.001609615,0.0001299535,0.0001014176,2.392534e-7,0.0001126044,0.09895424],"genre_scores_gemma":[0.998526,0.000004415191,0.0002138777,0.001002804,0.0001973155,0.000004174295,0.000001127601,0.000007349208,0.00004295853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.178272,"threshold_uncertainty_score":0.6397077,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2118059401","doi":"10.1287/mksc.1120.0723","title":"Can Brand Extension Signal Product Quality?","year":2012,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Argument (complex analysis); Product (mathematics); Quality (philosophy); Brand extension; Pooling; Extension (predicate logic); Economics; Microeconomics; Bayesian game; Observability; Mathematical economics; Computer science; Econometrics; Marketing; Mathematics; Brand awareness; Business; Game theory; Repeated game","retraction":null,"screen_n_in":null,"score":{"opus":0.036149061105759,"gpt":0.2813675028195449,"spread":0.2452184417137859,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01117546,0.0001485244,0.0001470096,0.0002722721,0.0006966681,0.0004281909,0.0003794204,0.00002262813,0.0004354292],"category_scores_gemma":[0.001519272,0.0001309469,0.000047207,0.001173354,0.0002612351,0.00168485,0.0003216992,0.0001360946,0.00008337417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000032082,"about_ca_system_score_gemma":0.00004816935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006159021,"about_ca_topic_score_gemma":0.0000445497,"domain_scores_codex":[0.998054,0.00004956979,0.0002510414,0.000396936,0.0005874775,0.0006609613],"domain_scores_gemma":[0.999102,0.0001729328,0.0001613252,0.0003272196,0.000197619,0.00003890956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005399955,0.00005329157,0.8159886,0.00008293219,0.000002006773,0.000001955444,0.00009133991,0.000002199172,0.06022307,0.0006406757,0.0007089573,0.122151],"study_design_scores_gemma":[0.0001549202,0.000001840453,0.9866664,0.00005587604,0.0000221963,0.000005014635,0.0001274854,0.0002833767,0.0005627288,0.00007355118,0.0117913,0.0002552708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9582236,0.0001535877,0.0000403111,0.0007934608,0.0007592403,0.0001580639,5.62296e-7,0.0001309033,0.03974021],"genre_scores_gemma":[0.9977786,0.000002291805,0.0002674214,0.0006758184,0.0008269947,0.000006490382,0.000002066845,0.00001368524,0.0004266328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1706778,"threshold_uncertainty_score":0.5358278,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2103048805","doi":"10.1287/mksc.2014.0885","title":"A Dynamic Model of Rational Addiction: Evaluating Cigarette Taxes","year":2015,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":64,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Consumption (sociology); Economics; Microeconomics; Addiction; Elasticity of substitution; Construct (python library); Addictive behavior; Public economics; Production (economics); Computer science; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.05260910720348395,"gpt":0.2961799407443956,"spread":0.2435708335409116,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007616175,0.0001117586,0.0001265524,0.0003022015,0.0003104831,0.0002257052,0.0003676441,0.00002745614,0.0001207231],"category_scores_gemma":[0.002390839,0.0001083726,0.00004223956,0.0009832481,0.000253442,0.001189658,0.0002560727,0.0001032074,0.00001326315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005283502,"about_ca_system_score_gemma":0.0002349064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009671848,"about_ca_topic_score_gemma":0.00003243406,"domain_scores_codex":[0.9982228,0.00002636096,0.0002842809,0.0003107211,0.0008906313,0.0002651595],"domain_scores_gemma":[0.9988016,0.000120827,0.0002443753,0.000215201,0.0005941797,0.00002374086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006894154,0.000227613,0.3589264,0.0003120038,0.00004003291,0.000009103963,0.0007703587,0.04381037,0.1155371,0.004816053,0.007362335,0.4674991],"study_design_scores_gemma":[0.0002579747,0.000005211213,0.05479112,0.00007841294,0.00003764024,0.00000181795,0.0001412209,0.9436299,0.00005414028,0.0005595506,0.0002968271,0.0001461826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9640636,0.00006433552,0.001680795,0.0003089986,0.0003697013,0.0001285387,0.000003656476,0.00007655537,0.03330386],"genre_scores_gemma":[0.9964256,0.000001087692,0.002882805,0.0002028865,0.00008814274,0.00001092511,0.000004632056,0.000009841733,0.0003741166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8998196,"threshold_uncertainty_score":0.4419306,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2123919220","doi":"10.1287/mksc.1100.0562","title":"Stock Market Response to Regulatory Reports of Deceptive Advertising: The Moderating Effect of Omission Bias and Firm Reputation","year":2010,"lang":"en","type":"article","venue":"Marketing Science","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","cited_by":64,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"University at Buffalo","keywords":"Reputation; Commission; Business; Stock (firearms); Stock market; Event study; Abnormal return; Context (archaeology); Economics; Marketing; Stock exchange; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.006534193929390688,"gpt":0.232862194126305,"spread":0.2263280001969143,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02193695,0.0001670269,0.0002190907,0.0002697917,0.0005454081,0.0002056937,0.0003387392,0.00004259283,0.00005763648],"category_scores_gemma":[0.1365062,0.00012606,0.00004705923,0.001009594,0.0004164348,0.0008116339,0.0005756012,0.0001979778,0.000001999996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003400197,"about_ca_system_score_gemma":0.00005405477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001064921,"about_ca_topic_score_gemma":0.00001829549,"domain_scores_codex":[0.9977117,0.0001607301,0.0004971653,0.0005306155,0.0008025231,0.0002972632],"domain_scores_gemma":[0.9908437,0.001271458,0.007069308,0.0004897599,0.0002989731,0.00002680042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001893468,0.00002894171,0.2905358,0.0004655556,0.00001308552,0.00001682592,0.0006693774,0.001055508,0.4858645,0.0001858944,0.002331089,0.21694],"study_design_scores_gemma":[0.0002503565,0.00004951598,0.9657437,0.0004483118,0.00003042586,0.000009247013,0.0001751699,0.02249514,0.007798075,0.0001223628,0.002679638,0.000198109],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901179,0.00001723442,0.003381961,0.0003701936,0.0002671067,0.0004596339,5.144002e-7,0.0000472482,0.005338205],"genre_scores_gemma":[0.9978392,0.000001018996,0.001381441,0.0001350691,0.00009324144,0.00001347463,5.382187e-7,0.00001751614,0.0005185424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6752079,"threshold_uncertainty_score":0.8707674,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2123792499","doi":"10.1287/mksc.2015.0921","title":"The “Peter Pan Syndrome” in Emerging Markets: The Productivity-Transparency Trade-off in IT Adoption","year":2015,"lang":"en","type":"article","venue":"Marketing Science","topic":"Taxation and Compliance Studies","field":"Economics, Econometrics and Finance","cited_by":62,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of Toronto","keywords":"Transparency (behavior); Productivity; Enforcement; Business; Audit; Language change; Emerging markets; Industrial organization; Economics; International economics; Accounting; Finance; Economic growth; Law","retraction":null,"screen_n_in":null,"score":{"opus":0.04417263294023258,"gpt":0.2499675134705381,"spread":0.2057948805303055,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009928665,0.0001003773,0.0001492675,0.0001673993,0.0003751128,0.0001501073,0.0005031202,0.00002156262,0.00001520498],"category_scores_gemma":[0.001716443,0.00007457264,0.00003113368,0.001144785,0.0003270849,0.0003520586,0.0000742436,0.0001798825,0.00003507372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001460499,"about_ca_system_score_gemma":0.00004399827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006251212,"about_ca_topic_score_gemma":0.0003784249,"domain_scores_codex":[0.9985936,0.00009282424,0.0004173747,0.0004064159,0.000113781,0.0003760407],"domain_scores_gemma":[0.9992415,0.0001860662,0.0002050889,0.0003073991,0.00002322306,0.00003676168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007373273,0.00008682061,0.9490243,0.00002615995,0.000006881487,0.000007192196,0.005344498,0.0003410266,0.00002391902,0.00805142,0.0009603064,0.03605369],"study_design_scores_gemma":[0.0001709156,0.00001277508,0.9707043,0.00004255996,6.501697e-7,0.000005793293,0.001351453,0.001502037,0.000003816798,0.001595967,0.02449396,0.0001158106],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9285733,0.001913977,0.0001190533,0.0181602,0.000687561,0.0002841799,0.000004141228,0.00002388113,0.05023378],"genre_scores_gemma":[0.9989852,0.0002216715,0.0001328357,0.000129396,0.00002916393,0.00003519278,3.344923e-7,0.000006079422,0.0004601195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07041198,"threshold_uncertainty_score":0.3441097,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3123828110","doi":"10.1287/mksc.2016.1020","title":"Measuring and Understanding Brand Value in a Dynamic Model of Brand Management","year":2017,"lang":"en","type":"article","venue":"Marketing Science","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":59,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Brand equity; Brand management; Advertising; Brand awareness; Business; Value (mathematics); Brand extension; Marketing; Economics; Mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.06721910574738194,"gpt":0.2595123016924768,"spread":0.1922931959450949,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004920664,0.0001295206,0.000175516,0.0004646009,0.0008174385,0.0007183081,0.0005395179,0.00002635182,0.00001137608],"category_scores_gemma":[0.0004062661,0.0001292917,0.00003052769,0.0003068142,0.0004222677,0.001354397,0.0006296649,0.0001005332,0.000001444987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007112655,"about_ca_system_score_gemma":0.00002361026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003288262,"about_ca_topic_score_gemma":0.0001965773,"domain_scores_codex":[0.9986256,0.00001534132,0.0002420986,0.0003823497,0.0003946546,0.0003399531],"domain_scores_gemma":[0.999256,0.00008025069,0.0002345049,0.0003678255,0.00004462507,0.0000168452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002751675,0.00006377553,0.9040439,0.00113935,0.0000148806,0.00002487009,0.0003131818,0.001617968,0.01660006,0.01155015,0.00001670375,0.06434001],"study_design_scores_gemma":[0.0007348864,0.000001716316,0.5682583,0.0004973488,0.00003436231,0.000001505592,0.0003150261,0.4268221,0.00003638705,0.003073211,0.00002307999,0.0002019919],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9331595,0.00005088951,0.001608061,0.0001748786,0.0001329788,0.0001756922,5.487084e-7,0.00002515018,0.06467235],"genre_scores_gemma":[0.999112,0.00002668541,0.0006768439,0.00004200455,0.00001678554,0.000004442712,2.657333e-7,0.00001081464,0.0001102312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4252042,"threshold_uncertainty_score":0.6926662,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2139669561","doi":"10.1287/mksc.2013.0784","title":"Returns Policies Between Channel Partners for Durable Products","year":2013,"lang":"en","type":"article","venue":"Marketing Science","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":59,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Durable good; Valuation (finance); Channel coordination; Microeconomics; Obsolescence; Economics; Product (mathematics); Incentive; Business; Industrial organization; Transaction cost; Supply chain; Marketing; Supply chain management; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.03856156788034253,"gpt":0.2642806846742918,"spread":0.2257191167939493,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002966363,0.0001585152,0.0001508826,0.0003358122,0.0006489968,0.0009157759,0.0006427087,0.00002777323,0.0001937645],"category_scores_gemma":[0.001657952,0.000138239,0.00004641273,0.001114187,0.00029848,0.001872446,0.0003140263,0.00006862469,0.0002354418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005182633,"about_ca_system_score_gemma":0.0000335268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004307663,"about_ca_topic_score_gemma":0.00001192113,"domain_scores_codex":[0.998199,0.00001232938,0.0002311838,0.0004754043,0.0004066941,0.0006753189],"domain_scores_gemma":[0.9990559,0.00009619832,0.0001645964,0.0003276223,0.0003285837,0.0000271378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006551136,0.0001595917,0.1246193,0.001927396,0.00005500232,0.000002832634,0.0008511565,0.0002162734,0.01063474,0.02669308,0.8100427,0.02473239],"study_design_scores_gemma":[0.0008515543,0.00003479216,0.323081,0.0002317808,0.00006761531,8.499212e-7,0.004076813,0.02519941,0.001755388,0.007633291,0.6360159,0.001051671],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8022999,0.00005559218,0.0002550887,0.01843161,0.001291403,0.001818373,0.000002446662,0.0003855037,0.1754601],"genre_scores_gemma":[0.9909718,0.000002624435,0.0004651264,0.001942838,0.001498407,0.0001502332,0.000008336533,0.00001944312,0.004941172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1984616,"threshold_uncertainty_score":0.8830848,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}