{"meta":{"query_hash":"4a602c2b4263","filters":{"venue":"Tourism Economics"},"cohort_total":33,"direct_labels_cover":0,"predictions_cover":33,"exported":33,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/4a602c2b4263","api":"https://metacan.xera.ac/api/v1/cohort?venue=Tourism+Economics"},"results":[{"id":"W1965351457","doi":"10.5367/000000001101297720","title":"Benchmarking an Emerging Lodging Alternative in Canada: A Profile of the B&amp;B Sector","year":2001,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Benchmarking; Popularity; Accommodation; Business; Marketing; Hospitality industry; Tourism; Baseline (sea); Economics; Industrial organization; Geography; Political science","score_opus":0.03644105058364954,"score_gpt":0.22924217513355505,"score_spread":0.1928011245499055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965351457","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992038,0.0003207527,0.00014890278,0.0002536782,0.000003968719,0.000032759952,0.0011783977,0.0000099751405,0.006013429],"genre_scores_gemma":[0.9959143,0.00048036096,0.00025889906,0.000058288653,0.0000018806408,0.000005413449,0.0009051097,0.000005802944,0.0023698995],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990823,0.000032785814,0.000022850696,0.00006734967,0.00044689962,0.00034784985],"domain_scores_gemma":[0.9974688,0.000097397016,0.0002613232,0.00004212558,0.0013996998,0.00073059194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005686447,0.00023727847,0.00020522671,0.002174337,0.0026957686,0.002001779,0.00068787934,0.0002653573,0.0017724717],"category_scores_gemma":[0.0013871368,0.00013399527,0.0001947992,0.0065704933,0.0007985613,0.0005532781,0.0009068625,0.00040205382,0.00021156155],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022006112,0.00012550727,0.91883117,0.00013042941,0.000022438036,0.0006805474,0.0081951935,0.0007139428,0.0028822084,0.0015901631,0.003619246,0.06298926],"study_design_scores_gemma":[0.0000021558526,0.00004385937,0.97971785,0.000026566331,0.0000065706886,0.00009008332,0.0130768195,0.0007970538,0.00034587606,0.000048434966,0.0058293967,0.000015322936],"about_ca_topic_score_codex":0.98631173,"about_ca_topic_score_gemma":0.9955545,"teacher_disagreement_score":0.023958834,"about_ca_system_score_codex":0.023958834,"about_ca_system_score_gemma":0.02380219,"threshold_uncertainty_score":0.17383432},"labels":[],"label_agreement":null},{"id":"W2014016271","doi":"10.5367/000000008783554884","title":"Fractional Integration and Structural Breaks: Evidence from International Monthly Arrivals in the USA","year":2008,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Structural break; Mean reversion; Series (stratigraphy); Economics; Econometrics; Shock (circulatory); Terrorism; Geography; Geology","score_opus":0.06171875499288534,"score_gpt":0.2514448800271067,"score_spread":0.18972612503422134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014016271","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946877,0.00021885849,0.002533379,0.00041709348,0.00001802269,0.000008361419,0.0002653378,0.000020547825,0.0018307521],"genre_scores_gemma":[0.9988814,0.00017220777,0.00034514273,0.00003093115,0.000020167477,0.0000057957445,0.00031224373,0.0000051642805,0.0002269086],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992531,0.0002590728,0.000056841636,0.00012735535,0.00016551114,0.00013815897],"domain_scores_gemma":[0.99194455,0.0028606956,0.0034709272,0.00069885876,0.0006050637,0.00041991594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020265316,0.00028922566,0.00053913955,0.0013395464,0.00070151925,0.0018561753,0.00066437066,0.00083549705,0.0023817127],"category_scores_gemma":[0.011033513,0.00023183756,0.0005304208,0.0031776873,0.0006850646,0.0014308998,0.0009525248,0.0016759878,0.00033929016],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008467292,0.00041208277,0.9030772,0.00006808908,0.00035656808,0.0005450746,0.0031990504,0.02469322,0.0009360977,0.013446706,0.0034754288,0.048943665],"study_design_scores_gemma":[0.000052028805,0.00018350733,0.8587736,0.000060848204,0.00013958372,0.00016429673,0.003311792,0.11628798,0.0005358328,0.016144253,0.004283215,0.000063013846],"about_ca_topic_score_codex":0.02835252,"about_ca_topic_score_gemma":0.029190345,"teacher_disagreement_score":0.02835252,"about_ca_system_score_codex":0.0008077175,"about_ca_system_score_gemma":0.00041233012,"threshold_uncertainty_score":0.056375027},"labels":[],"label_agreement":null},{"id":"W2020075915","doi":"10.5367/te.2012.0102","title":"Modelling International Tourism Demand for the Caribbean","year":2012,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Distributed lag; Economics; Cointegration; Revenue; Visitor pattern; Econometric model; Demand shock; Economy; Econometrics; Macroeconomics; Finance; Geography","score_opus":0.05836045145888089,"score_gpt":0.3193867258786089,"score_spread":0.261026274419728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020075915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93596536,0.0007261661,0.015538188,0.0014346854,0.000039677543,0.00008103194,0.0024697748,0.00010633807,0.0436387],"genre_scores_gemma":[0.9860763,0.0004827366,0.0017357224,0.000058337777,0.000010950498,0.00007463914,0.000834265,0.00004025247,0.010686874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975866,0.00008456493,0.000009239338,0.000037973776,0.00003496607,0.00007457571],"domain_scores_gemma":[0.9996512,0.00015485747,0.000053634776,0.00002147779,0.000073591924,0.00004515114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041832705,0.0008578606,0.00051672844,0.0007279349,0.0005886371,0.0022137824,0.0011014065,0.0014187247,0.0048633935],"category_scores_gemma":[0.0019399195,0.00045565242,0.0008267396,0.0013015802,0.00037914774,0.00097121886,0.0008547039,0.00084801373,0.0004154544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007793836,0.000085704734,0.00826285,0.00006701544,0.000051637624,0.00023373651,0.00030675513,0.9732111,0.0006016384,0.012173802,0.0014663618,0.0034613763],"study_design_scores_gemma":[0.000014249454,0.000027882743,0.0024485975,0.00001587808,0.000018327464,0.000019553781,0.00036186125,0.99357635,0.00008912952,0.0014434309,0.001966211,0.000018549908],"about_ca_topic_score_codex":0.3920541,"about_ca_topic_score_gemma":0.264791,"teacher_disagreement_score":0.3920541,"about_ca_system_score_codex":0.0038574482,"about_ca_system_score_gemma":0.0017957593,"threshold_uncertainty_score":0.77954423},"labels":[],"label_agreement":null},{"id":"W2030458677","doi":"10.5367/000000007779784524","title":"Resorts, Culture, and Music: The Cape Breton Tourism Cluster","year":2007,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Cape Breton University","funders":"","keywords":"Tourism; Nova scotia; Cape; Cluster development; Investment (military); Government (linguistics); Economic geography; Business; Cluster (spacecraft); Economic growth; Economy; Scale (ratio); Geography; Political science; Economics; Archaeology","score_opus":0.024702801286827,"score_gpt":0.28988520346782654,"score_spread":0.26518240218099953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030458677","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96908575,0.0008583375,0.000038441318,0.0019834526,0.000042234264,0.000031417407,0.00017353956,0.000002674802,0.027784158],"genre_scores_gemma":[0.98965704,0.0007865751,0.00006421127,0.00016077432,0.000015227302,0.000013729683,0.00008627562,0.000003829997,0.009212264],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9997298,0.000054835855,0.000005717936,0.0000220878,0.000072397626,0.000115187075],"domain_scores_gemma":[0.9992254,0.00008591888,0.00010169488,0.000021278789,0.00010069278,0.00046508253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024314683,0.00013504503,0.00017851761,0.0012351478,0.0045838878,0.002517702,0.0004961073,0.00036219813,0.0064332606],"category_scores_gemma":[0.0011831197,0.00013283367,0.00006680145,0.003265681,0.001783191,0.00066009414,0.0021741996,0.00053173536,0.00026876558],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048544153,0.00022580165,0.51820153,0.00033833832,0.000067368506,0.009890337,0.2787841,0.0005345839,0.0023269504,0.020388123,0.046664648,0.12209279],"study_design_scores_gemma":[0.000011463167,0.00005383806,0.7720786,0.00015264834,0.000009655099,0.0004913776,0.19672759,0.00017995687,0.00006012012,0.0005896762,0.029621437,0.0000236134],"about_ca_topic_score_codex":0.74079466,"about_ca_topic_score_gemma":0.9309976,"teacher_disagreement_score":0.25920534,"about_ca_system_score_codex":0.008790257,"about_ca_system_score_gemma":0.005649101,"threshold_uncertainty_score":0.5214637},"labels":[],"label_agreement":null},{"id":"W2031583687","doi":"10.5367/000000007779784443","title":"Resource Dependency, Costs and Revenues of a Street Festival","year":2007,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Nonprofit Sector and Volunteering","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Tourism; Revenue; Stakeholder; Context (archaeology); Dependency (UML); Position (finance); Resource dependence theory; Business; Resource (disambiguation); Bargaining power; Relative price; Stakeholder theory; Marketing; Music festival; Economics; Industrial organization; Microeconomics; Finance; Geography; Management","score_opus":0.0161520934575736,"score_gpt":0.279773867598032,"score_spread":0.2636217741404584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031583687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99661875,0.00003093962,0.00004882819,0.000086480686,0.0000028853049,0.0000027927756,0.00004942638,7.5082784e-7,0.0031591337],"genre_scores_gemma":[0.9996069,0.000023249322,0.00002065368,0.0000028906954,0.0000031948025,0.0000017619027,0.00003739039,7.243395e-7,0.00030327213],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994804,0.00017588964,0.00002601622,0.00002844886,0.00009771609,0.00019155946],"domain_scores_gemma":[0.99539727,0.0014560239,0.0014358694,0.00009331407,0.0002982908,0.0013191706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073333946,0.00013435684,0.00016954601,0.0011373813,0.0012732114,0.0014187639,0.00032922896,0.00029351693,0.004454309],"category_scores_gemma":[0.0050301673,0.00011746557,0.00016986884,0.00067247107,0.0009814341,0.0009182719,0.0013672581,0.0006591179,0.00029273052],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056644506,0.0003780933,0.9612561,0.000051079478,0.000052387528,0.0016538533,0.002905306,0.004317337,0.0010781809,0.007016911,0.001379171,0.019345116],"study_design_scores_gemma":[0.0000050469803,0.000115786344,0.9868482,0.000017170252,0.000009265165,0.00032775532,0.008376768,0.0012721561,0.0001422862,0.001304146,0.0015663884,0.000015032093],"about_ca_topic_score_codex":0.008068839,"about_ca_topic_score_gemma":0.022059925,"teacher_disagreement_score":0.008068839,"about_ca_system_score_codex":0.001879445,"about_ca_system_score_gemma":0.000617293,"threshold_uncertainty_score":0.016043723},"labels":[],"label_agreement":null},{"id":"W2033443192","doi":"10.5367/0000000041895049","title":"Forecasting Inbound Canadian Tourism: An Evaluation of Error Corrections Model Forecasts","year":2004,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Wine Industry and Tourism","field":"Business, Management and Accounting","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Brock University","funders":"","keywords":"Univariate; Econometrics; Forecast error; Multivariate statistics; Tourism; Econometric model; Regression; Regression analysis; Consensus forecast; Mean absolute error; Forecast verification; Statistics; Mean squared error; Economics; Computer science; Mathematics; Geography","score_opus":0.10766849153661646,"score_gpt":0.2659660752644275,"score_spread":0.15829758372781105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033443192","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9382006,0.0015037205,0.04183761,0.0010880404,0.00020861508,0.00013370055,0.0024874848,0.0010882159,0.013452013],"genre_scores_gemma":[0.9810333,0.00057031953,0.015218164,0.000053166394,0.000037489797,0.000022217988,0.0015735304,0.00005194842,0.001439896],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99801624,0.0005896491,0.00008726396,0.00016182306,0.00097520347,0.00016989521],"domain_scores_gemma":[0.99472624,0.0023458963,0.00038702047,0.0002710002,0.0021086636,0.00016111236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033809606,0.0012896096,0.000757838,0.0014889643,0.0006133275,0.0012830776,0.0010530881,0.00058193743,0.00083181116],"category_scores_gemma":[0.010553994,0.00024596302,0.0005239115,0.0018064857,0.00029175004,0.0010980923,0.00046334256,0.00063398015,0.00012791484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036117854,0.000065508946,0.020870205,0.0001094699,0.0001661745,0.00012407333,0.00008088078,0.9258891,0.0010031359,0.0016399999,0.001964219,0.047726095],"study_design_scores_gemma":[0.000042196396,0.00014186208,0.018758072,0.000020865393,0.000064707085,0.00003890945,0.00011131156,0.9764361,0.0019656578,0.00041000618,0.001969419,0.000040901617],"about_ca_topic_score_codex":0.7272305,"about_ca_topic_score_gemma":0.6454168,"teacher_disagreement_score":0.2727695,"about_ca_system_score_codex":0.0042543407,"about_ca_system_score_gemma":0.004483849,"threshold_uncertainty_score":0.5487518},"labels":[],"label_agreement":null},{"id":"W2040987091","doi":"10.5367/000000001101297919","title":"International Boundaries and Tourism Strategies","year":2001,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Gambling Behavior and Treatments","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Entertainment; Currency; Marketing; Competition (biology); Business; Economics; Economic geography; Economy; Political science","score_opus":0.05305881069187081,"score_gpt":0.3410623569997741,"score_spread":0.2880035463079033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040987091","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016959583,0.0015864244,0.0004505392,0.0031233607,0.00010252743,0.000017397684,0.00002325775,0.000009079845,0.9777278],"genre_scores_gemma":[0.852967,0.0035904997,0.0009291481,0.0017551754,0.00009672038,0.00008224035,0.00012811157,0.00004956165,0.14040159],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9991885,0.00029809916,0.000027167034,0.000084847576,0.00009558903,0.00030575308],"domain_scores_gemma":[0.99925107,0.00009429856,0.000097351134,0.00005643501,0.00011173621,0.000389174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008438616,0.00027903105,0.0001970884,0.00096361665,0.0054137255,0.0075241816,0.0004972943,0.0010698707,0.020250684],"category_scores_gemma":[0.0015236326,0.00010003471,0.00018421811,0.0013666501,0.007882048,0.0029837722,0.004594943,0.001493965,0.0012389856],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011570606,0.000024286048,0.0016339191,0.000030856365,0.0000044388453,0.00014160368,0.0074798632,0.00011831679,0.000042681186,0.9590163,0.010502336,0.020993806],"study_design_scores_gemma":[0.000016407545,0.000042838168,0.0077630705,0.00040949296,0.00000762738,0.00032415995,0.057374455,0.00024495865,0.00009032063,0.16158989,0.77211595,0.00002098535],"about_ca_topic_score_codex":0.022899898,"about_ca_topic_score_gemma":0.046149954,"teacher_disagreement_score":0.022899898,"about_ca_system_score_codex":0.0038761254,"about_ca_system_score_gemma":0.0031492095,"threshold_uncertainty_score":0.06774527},"labels":[],"label_agreement":null},{"id":"W2045207766","doi":"10.5367/000000002101298089","title":"International Tourism in 2001, and Tracking Trends in Travel and Tourism with Seasonal Adjustment","year":2002,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Seasonal adjustment; Seasonality; Economics; Geography; Regional science; Statistics","score_opus":0.03810469787744739,"score_gpt":0.28761459470795847,"score_spread":0.24950989683051109,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045207766","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97324526,0.00029508368,0.00076299394,0.00023905697,0.00005870317,0.000051591145,0.016332258,0.00005555843,0.00895954],"genre_scores_gemma":[0.96960604,0.0006028621,0.0014994988,0.000068811496,0.00004943471,0.00009259335,0.022576813,0.000031372998,0.0054723965],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971694,0.00005017207,0.000046233556,0.00007517282,0.00007296597,0.000038485217],"domain_scores_gemma":[0.9988011,0.0001351277,0.00050770404,0.000100131874,0.00030982526,0.0001460778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059229176,0.0003167339,0.00015943979,0.0024063888,0.00029611881,0.0012259528,0.00025887252,0.00041434457,0.001500445],"category_scores_gemma":[0.0031975114,0.00015562463,0.00021578229,0.0051489673,0.0001815406,0.0009837628,0.00061346166,0.00065739546,0.0005438409],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029729548,0.00014334897,0.95585597,0.00006346577,0.00006210685,0.000104122526,0.000922113,0.0027941687,0.0003284224,0.00060928456,0.0066968463,0.032122944],"study_design_scores_gemma":[0.0000031583834,0.0000801823,0.99212897,0.00001450929,0.000016450604,0.000086385604,0.00066247466,0.0020524308,0.000083348335,0.00010012346,0.004764199,0.000007785463],"about_ca_topic_score_codex":0.03373566,"about_ca_topic_score_gemma":0.07633196,"teacher_disagreement_score":0.03373566,"about_ca_system_score_codex":0.000629063,"about_ca_system_score_gemma":0.00036951283,"threshold_uncertainty_score":0.06707859},"labels":[],"label_agreement":null},{"id":"W2055155854","doi":"10.5367/000000009788254340","title":"Predicting Quarterly Hong Kong Tourism Demand Growth Rates, Directional Changes and Turning Points with Composite Leading Indicators","year":2009,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Turning point; Autoregressive integrated moving average; Econometrics; Quarter (Canadian coin); Economics; Point (geometry); Performance indicator; Statistics; Time series; Mathematics; Geography","score_opus":0.027512825805205587,"score_gpt":0.2892152628314716,"score_spread":0.261702437026266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055155854","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958752,0.000030340681,0.0027300757,0.000040966934,0.000013188438,0.000009884939,0.0005107684,0.000032843538,0.0007566668],"genre_scores_gemma":[0.9969658,0.000050689687,0.0012199403,0.0000063745792,0.0000035773294,0.000006684102,0.0008891126,0.000003971069,0.0008537703],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987006,0.00003434641,0.000009566531,0.000026526528,0.00003168675,0.000027844748],"domain_scores_gemma":[0.999276,0.0002587059,0.00008660869,0.00007664549,0.00022177071,0.00008024216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007411195,0.00035422944,0.00026648777,0.0005092497,0.0001454731,0.0005264713,0.0002574594,0.00018245862,0.0008869603],"category_scores_gemma":[0.0017826367,0.00015671375,0.00036256676,0.0006172933,0.0001456616,0.00033272797,0.0002561473,0.00034149308,0.00031144137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044854623,0.00022593384,0.5963207,0.00006299752,0.00009918475,0.0002913073,0.0002090859,0.35562405,0.0014812738,0.00079173985,0.0028696817,0.041575413],"study_design_scores_gemma":[0.000010509184,0.00012179635,0.18107042,0.000011384104,0.000024079036,0.000026775606,0.0002588992,0.8163675,0.0010788229,0.00027867928,0.0007314416,0.000019769115],"about_ca_topic_score_codex":0.105173394,"about_ca_topic_score_gemma":0.0935456,"teacher_disagreement_score":0.105173394,"about_ca_system_score_codex":0.0008798762,"about_ca_system_score_gemma":0.0007837531,"threshold_uncertainty_score":0.20912248},"labels":[],"label_agreement":null},{"id":"W2062507696","doi":"10.5367/0000000041895030","title":"Tourist Typology: An Ex Ante Approach","year":2004,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Tourism; Typology; Ex-ante; Marketing; Set (abstract data type); Factory (object-oriented programming); Business; Advertising; Economics; Computer science; Geography","score_opus":0.038325313563777025,"score_gpt":0.31948726880809475,"score_spread":0.28116195524431775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062507696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72879356,0.00083481264,0.120950244,0.0030667346,0.0004795755,0.0016035658,0.0028047173,0.00007507019,0.14139174],"genre_scores_gemma":[0.9588576,0.0003239791,0.030421918,0.00018868575,0.00012771768,0.0014590833,0.0011991869,0.000024923067,0.007396923],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9916459,0.00514026,0.0005505167,0.0006272572,0.001535281,0.0005008132],"domain_scores_gemma":[0.9792628,0.0092287185,0.003978953,0.0024171649,0.004510345,0.0006020076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009184113,0.00070553465,0.00069095165,0.009768694,0.0025608256,0.0067685167,0.002145547,0.0008269512,0.014452612],"category_scores_gemma":[0.021760952,0.0004151687,0.00078758714,0.006285722,0.0044994415,0.00653432,0.003971655,0.0015214238,0.0011361348],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005036722,0.00052990613,0.3493941,0.00078808074,0.00018138852,0.00092152494,0.023999963,0.0039864318,0.0014754111,0.4841352,0.0048068357,0.12927744],"study_design_scores_gemma":[0.00013188702,0.0015895223,0.35671827,0.00080107444,0.00019265768,0.002372775,0.23273592,0.046952493,0.003579962,0.25559738,0.099077456,0.00025068191],"about_ca_topic_score_codex":0.0020431215,"about_ca_topic_score_gemma":0.0025757195,"teacher_disagreement_score":0.014452612,"about_ca_system_score_codex":0.0045658927,"about_ca_system_score_gemma":0.001960286,"threshold_uncertainty_score":0.048570752},"labels":[],"label_agreement":null},{"id":"W2065868901","doi":"10.5367/te.2013.0250","title":"The Income Elasticity of Demand and Firm Performance of US Restaurant Companies by Restaurant Type during Recessions","year":2013,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Recession; Income elasticity of demand; Newspaper; Economics; Price elasticity of demand; Elasticity (physics); Business; Labour economics; Advertising; Microeconomics; Macroeconomics","score_opus":0.008136099524502904,"score_gpt":0.17206172716250845,"score_spread":0.16392562763800556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065868901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99926585,0.000031405412,0.000029246996,0.000036149126,0.0000012877664,0.0000017352357,0.00033188585,0.0000015565043,0.00030079792],"genre_scores_gemma":[0.9989888,0.000028845157,0.000014895813,0.00001190821,0.0000023661744,0.000001867943,0.0007269273,0.0000011086674,0.00022328756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996425,0.000064709944,0.00003743361,0.0000539193,0.000064283384,0.00013716694],"domain_scores_gemma":[0.9946626,0.001391286,0.0022991558,0.00026957318,0.00054319284,0.00083430717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007700198,0.00016932403,0.00022211521,0.00086478743,0.000278302,0.0008414881,0.00028300888,0.00039933945,0.002690258],"category_scores_gemma":[0.0035314218,0.00018119821,0.00055213907,0.001113986,0.0003045677,0.0004576639,0.00062191125,0.0006615155,0.0005001108],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014111582,0.000045166944,0.99817646,0.0000035161713,0.000038100927,0.00003723962,0.000084129686,0.00037266553,0.0001811215,0.000039623796,0.00014965975,0.0007311929],"study_design_scores_gemma":[0.0000013255191,0.000018839759,0.99931204,0.0000013193697,0.0000058082555,0.000013270287,0.0002414948,0.0002951768,0.00004015742,0.000011843226,0.00005617351,0.0000024794015],"about_ca_topic_score_codex":0.03959645,"about_ca_topic_score_gemma":0.042359024,"teacher_disagreement_score":0.03959645,"about_ca_system_score_codex":0.00072313094,"about_ca_system_score_gemma":0.00024764173,"threshold_uncertainty_score":0.078731894},"labels":[],"label_agreement":null},{"id":"W2074379351","doi":"10.5367/000000008785633541","title":"The Economics of Regulation and Taxation Policies for Casino Tourism","year":2008,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Gambling Behavior and Treatments","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Cartel; Economics; Investment (military); Tourism; Monopoly; Production (economics); Private sector; Public economics; Microeconomics; Incentive","score_opus":0.07663806919754461,"score_gpt":0.325016052365934,"score_spread":0.24837798316838938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074379351","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34513935,0.011420563,0.03975783,0.03515235,0.00048105646,0.00029010943,0.00033332134,0.000113740694,0.5673117],"genre_scores_gemma":[0.98240376,0.0019105176,0.0017707625,0.0012784794,0.00015026811,0.00006851326,0.000030798026,0.000010433897,0.0123765245],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99823487,0.00092904054,0.00003902669,0.0001309085,0.00028214414,0.00038399387],"domain_scores_gemma":[0.99600416,0.0023812423,0.0008769664,0.00021079996,0.00026256178,0.00026431362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023311335,0.00053858105,0.00053062354,0.001186436,0.0020262008,0.005819535,0.0006311653,0.004673992,0.009106329],"category_scores_gemma":[0.004950064,0.00046150511,0.0008649498,0.0008788271,0.0055113854,0.0027244864,0.0012661194,0.0032603631,0.00041776535],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008462816,0.00009675907,0.0014171111,0.000045953606,0.000024176183,0.000093565104,0.00010245254,0.010705263,0.00024822366,0.97986424,0.0018976312,0.005420003],"study_design_scores_gemma":[0.00020481047,0.00020191305,0.009229745,0.0003403405,0.00012928103,0.00019969528,0.0011305116,0.041263744,0.00063545094,0.9108881,0.03567359,0.00010284404],"about_ca_topic_score_codex":0.008520586,"about_ca_topic_score_gemma":0.011441421,"teacher_disagreement_score":0.009106329,"about_ca_system_score_codex":0.008531652,"about_ca_system_score_gemma":0.0033485196,"threshold_uncertainty_score":0.06190169},"labels":[],"label_agreement":null},{"id":"W2076951281","doi":"10.5367/000000009788254368","title":"Room Rates as Signals of Quality, Sell-Out Risk and the Prospects of Getting a Better Deal: Analytical Model and Empirical Evidence","year":2009,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Quality (philosophy); Context (archaeology); Imperfect; Revenue; Perfect information; Economics; Perception; Marketing; Business; Empirical evidence; Revenue management; Risk perception; Empirical research; Microeconomics; Econometrics; Finance","score_opus":0.08096207386824765,"score_gpt":0.328085405265109,"score_spread":0.24712333139686132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076951281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88762975,0.0046440363,0.07800749,0.0036146052,0.00005345319,0.00016340024,0.00047558558,0.00019912329,0.025212543],"genre_scores_gemma":[0.9905557,0.0022424748,0.0043483493,0.00012816931,0.000051448777,0.00003677404,0.00012621231,0.000018513983,0.0024923447],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990293,0.0004843992,0.000048319194,0.00016209226,0.00013756407,0.00013829437],"domain_scores_gemma":[0.95674115,0.035915542,0.004957707,0.00083924376,0.0010755118,0.00047075265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004045481,0.00095171056,0.0013425978,0.0019372902,0.00058182765,0.005479423,0.0019594904,0.0028918681,0.009223483],"category_scores_gemma":[0.021251692,0.0011409742,0.0017795295,0.0019900487,0.002425303,0.0041287574,0.0013947742,0.0019849818,0.0012190295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013653116,0.0014949536,0.1681162,0.0008310257,0.0010808571,0.001772296,0.0023558282,0.43119037,0.0026391135,0.32468447,0.0033997204,0.061069816],"study_design_scores_gemma":[0.00016813814,0.00024012136,0.026285848,0.000103192506,0.0007428089,0.00041218588,0.0009195167,0.8709195,0.00050612725,0.097922765,0.0016252701,0.00015451945],"about_ca_topic_score_codex":0.015512655,"about_ca_topic_score_gemma":0.0076710233,"teacher_disagreement_score":0.015512655,"about_ca_system_score_codex":0.0020997839,"about_ca_system_score_gemma":0.0010676028,"threshold_uncertainty_score":0.030855656},"labels":[],"label_agreement":null},{"id":"W2078618560","doi":"10.5367/te.2013.0184","title":"Estimating the Effects of Different Admission Fees on Revenues for a Mega-Event Using a Contingent Valuation Method","year":2013,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Revenue; Visitor pattern; Mega-; Valuation (finance); Willingness to pay; Event (particle physics); Population; Business; Constraint (computer-aided design); Contingent valuation; Quarter (Canadian coin); Economics; Finance; Geography; Demography; Microeconomics; Computer science","score_opus":0.08264554543809952,"score_gpt":0.2708654719679255,"score_spread":0.18821992652982597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078618560","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9467833,0.00015395693,0.049456622,0.00024077117,0.000024789068,0.00026509367,0.00055343105,0.00011099015,0.002410986],"genre_scores_gemma":[0.98859686,0.00007401402,0.010350134,0.000022671053,0.00000949341,0.00008319993,0.00027586645,0.0000072227845,0.00058041076],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952874,0.0029826204,0.00019536089,0.0005060481,0.00051110453,0.0005174033],"domain_scores_gemma":[0.9263114,0.06682432,0.00344062,0.0017032118,0.00093596993,0.00078449835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010673926,0.0007296712,0.0011202877,0.0015068062,0.0005759161,0.0016903324,0.0014876497,0.0013392562,0.0046966802],"category_scores_gemma":[0.04239349,0.0006461266,0.0020484251,0.0018529801,0.00080329744,0.0018992986,0.0011643254,0.0025978177,0.00027615315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019056279,0.0009109268,0.09074548,0.0001011258,0.00045609626,0.00039005507,0.00012945528,0.8569588,0.0016369309,0.011368676,0.000741165,0.034655612],"study_design_scores_gemma":[0.00007534741,0.00035711227,0.032677703,0.000013595459,0.00012795837,0.000050153052,0.000087531815,0.9625252,0.0008786234,0.002945617,0.0002224271,0.000038777605],"about_ca_topic_score_codex":0.017710142,"about_ca_topic_score_gemma":0.009949942,"teacher_disagreement_score":0.017710142,"about_ca_system_score_codex":0.0021474466,"about_ca_system_score_gemma":0.0014089275,"threshold_uncertainty_score":0.05644977},"labels":[],"label_agreement":null},{"id":"W2083637888","doi":"10.5367/000000008785633532","title":"Comparing Recreation Benefits from On-Site versus Household Surveys in Count Data Travel Cost Demand Models with Overdispersion","year":2008,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Overdispersion; Count data; Negative binomial distribution; Econometrics; Tourism; Visitor pattern; Survey data collection; Estimator; Recreation; Truncation (statistics); Statistics; Poisson distribution; Sample (material); Economics; Geography; Mathematics; Computer science","score_opus":0.32446687748297726,"score_gpt":0.22708399753018643,"score_spread":0.09738287995279082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083637888","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9426557,0.0002704087,0.053863473,0.00058588554,0.000047404577,0.00015707246,0.00035663426,0.00007079899,0.0019926485],"genre_scores_gemma":[0.98474634,0.00015954676,0.012674889,0.00010070081,0.0000376829,0.00011619644,0.00043356032,0.000029257268,0.0017018296],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9873416,0.010747274,0.00024382089,0.00056671625,0.0006603776,0.00044018877],"domain_scores_gemma":[0.84191465,0.1442049,0.0059917425,0.0049593057,0.0022743738,0.0006549887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02652811,0.00081276963,0.0014140414,0.0012224383,0.0004192023,0.0019128205,0.0021045844,0.0016412579,0.0026853113],"category_scores_gemma":[0.07285323,0.00079418375,0.0017845504,0.0016647571,0.001220168,0.0026131868,0.0020116628,0.0016109094,0.00032728867],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034517662,0.0013380358,0.1789955,0.00034318684,0.0011623881,0.00031731997,0.00070442853,0.73927236,0.0004916593,0.017775284,0.0014516056,0.05469641],"study_design_scores_gemma":[0.0001558703,0.0008927184,0.031244311,0.0000275033,0.0003324244,0.000072732866,0.00043046303,0.95663303,0.00044614403,0.009022415,0.0006784439,0.00006392599],"about_ca_topic_score_codex":0.013638528,"about_ca_topic_score_gemma":0.0087246075,"teacher_disagreement_score":0.02652811,"about_ca_system_score_codex":0.0018997389,"about_ca_system_score_gemma":0.0009225243,"threshold_uncertainty_score":0.14029568},"labels":[],"label_agreement":null},{"id":"W2143933527","doi":"10.5367/000000007780823159","title":"<i>Research Note:</i> Modelling Tourism Demand – an Econometric Analysis of North American Tourist Expenditure in Ireland, 1985–2004","year":2007,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Economics; Revenue; Irish; Earnings; Per capita; Econometric model; Exchequer; Value (mathematics); Econometric analysis; Exchange rate; Macroeconomics; Geography; Finance; Econometrics; Political science","score_opus":0.04502334142047075,"score_gpt":0.3530062814911809,"score_spread":0.30798294007071014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143933527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9826684,0.00028396942,0.00211989,0.0013504693,0.0000365268,0.000035323766,0.006417314,0.00006765357,0.0070204125],"genre_scores_gemma":[0.97773266,0.00044951422,0.0016139096,0.00016909176,0.00003749159,0.00004786489,0.008190467,0.000023890634,0.01173504],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997769,0.00006863152,0.000018276525,0.000040147148,0.00004047422,0.000055583158],"domain_scores_gemma":[0.99923396,0.00032521918,0.00019159753,0.000054470787,0.00014278323,0.000052041563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004944649,0.0002540389,0.00032759868,0.00087280653,0.00040147913,0.0011191505,0.0005432726,0.00040336812,0.0065840557],"category_scores_gemma":[0.0017416824,0.0002407404,0.0009575607,0.0014727665,0.00034067756,0.00042657187,0.0004974723,0.0007099105,0.001245183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027848434,0.0005622272,0.70678234,0.00023140419,0.00045301515,0.0008325416,0.0006346788,0.23732546,0.001254538,0.0036437986,0.030737543,0.017263921],"study_design_scores_gemma":[0.00004541549,0.00023234234,0.8224532,0.00014018083,0.00024295313,0.0001942441,0.004375299,0.14462532,0.0018037922,0.0011393464,0.024647592,0.00010030041],"about_ca_topic_score_codex":0.31452566,"about_ca_topic_score_gemma":0.40338302,"teacher_disagreement_score":0.31452566,"about_ca_system_score_codex":0.0023106302,"about_ca_system_score_gemma":0.0021157486,"threshold_uncertainty_score":0.6253898},"labels":[],"label_agreement":null},{"id":"W2144327320","doi":"10.5367/000000006777637412","title":"Effect of Demand Volume on Forecasting Accuracy","year":2006,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Econometrics; Tourism; Estimation; Volatility (finance); Population; Seasonality; Economics; Geography; Statistics; Mathematics","score_opus":0.02013442518403894,"score_gpt":0.29421396495549695,"score_spread":0.274079539771458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144327320","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9903661,0.00049902726,0.0049520233,0.00055874436,0.00010174355,0.000019079345,0.00057778694,0.0002490618,0.0026763096],"genre_scores_gemma":[0.9979412,0.00011527294,0.0007768345,0.000037367292,0.000042531614,0.000006140562,0.0007367484,0.000039274437,0.00030458608],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99340504,0.0032010565,0.0005816844,0.00083784456,0.0014497918,0.0005246113],"domain_scores_gemma":[0.79495686,0.18493864,0.0048456984,0.008099273,0.006116649,0.0010429114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013063326,0.0005872353,0.00085199944,0.0011918106,0.00036557118,0.0021842332,0.0006778806,0.0010262287,0.0016760278],"category_scores_gemma":[0.09183872,0.00044713682,0.0007968901,0.0012869806,0.00058119104,0.0033777682,0.0008900016,0.0013689538,0.00048335767],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033415775,0.00022405329,0.5609411,0.00013035529,0.00052874314,0.0004989498,0.0007007214,0.33559453,0.002628517,0.0010883602,0.0023049673,0.0920181],"study_design_scores_gemma":[0.00018911953,0.0014494223,0.31333917,0.00012882818,0.00038933774,0.00060718384,0.0010942023,0.6672311,0.007900181,0.004380442,0.0031340932,0.00015686397],"about_ca_topic_score_codex":0.0064810654,"about_ca_topic_score_gemma":0.003256818,"teacher_disagreement_score":0.013063326,"about_ca_system_score_codex":0.00060025824,"about_ca_system_score_gemma":0.00048131583,"threshold_uncertainty_score":0.06908631},"labels":[],"label_agreement":null},{"id":"W2144699373","doi":"10.5367/000000009789955116","title":"Effect of Seasonality Treatment on the Forecasting Performance of Tourism Demand Models","year":2009,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Seasonality; Unobservable; Econometrics; Tourism; Econometric model; Economics; Seasonal adjustment; Unit root; Time series; Statistics; Geography; Mathematics; Variable (mathematics)","score_opus":0.03091884628421165,"score_gpt":0.2254907719500669,"score_spread":0.19457192566585524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144699373","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9753612,0.0006996488,0.0215155,0.0004972634,0.00013581096,0.000022640146,0.00017989763,0.00019372671,0.0013942451],"genre_scores_gemma":[0.99666387,0.0001827099,0.00254301,0.000039864513,0.000026454785,0.0000065209106,0.00021690057,0.000019249184,0.00030148172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971354,0.002023631,0.00016371153,0.0002589062,0.00021478573,0.00020359295],"domain_scores_gemma":[0.9730294,0.022788422,0.0013194925,0.0013903237,0.0011558915,0.00031648326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009064404,0.0005357872,0.0006813428,0.00048580716,0.00038719922,0.0010402615,0.0003955205,0.000744169,0.0010452459],"category_scores_gemma":[0.029157808,0.00033597348,0.0007275493,0.0006095445,0.00043918993,0.0012017573,0.0004950282,0.0011180302,0.00020382363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032040821,0.00052286824,0.14878376,0.0002082748,0.00069195766,0.00035145535,0.00057564676,0.67953354,0.006636142,0.002779003,0.00194599,0.1547673],"study_design_scores_gemma":[0.000055963043,0.0007376179,0.034057137,0.000035837496,0.00017048104,0.00006455383,0.00029255083,0.95956814,0.0029861918,0.001328718,0.0006625282,0.0000403616],"about_ca_topic_score_codex":0.009527732,"about_ca_topic_score_gemma":0.0068124244,"teacher_disagreement_score":0.009527732,"about_ca_system_score_codex":0.00046816742,"about_ca_system_score_gemma":0.00079750473,"threshold_uncertainty_score":0.04793775},"labels":[],"label_agreement":null},{"id":"W2328026057","doi":"10.5367/te.2014.0402","title":"<i>Research Note:</i> Nowcasting Tourist Arrivals in Barbados – Just Google it!","year":2014,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Tourism; The Internet; Autoregressive model; Empirical evidence; Econometrics; Advertising; Regional science; Empirical research; Economics; Business; Computer science; Geography; World Wide Web; Statistics; Mathematics","score_opus":0.052062552191512436,"score_gpt":0.3518166956320248,"score_spread":0.2997541434405123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328026057","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43735364,0.011268036,0.007293694,0.2789062,0.010571403,0.00029724147,0.10876268,0.00095603167,0.14459112],"genre_scores_gemma":[0.8821516,0.008316672,0.009827839,0.015562379,0.0043426272,0.00013930953,0.030035947,0.00041213704,0.04921148],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991768,0.00020178476,0.000074363765,0.00015416835,0.0002799653,0.00011293695],"domain_scores_gemma":[0.9901007,0.0041620415,0.0015898787,0.0005292507,0.0031194855,0.0004986868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014344021,0.0002426961,0.00039711013,0.0021593662,0.0014406218,0.0028517477,0.00078853226,0.001202658,0.016180813],"category_scores_gemma":[0.012773201,0.00014503059,0.0005561111,0.005498732,0.00063093216,0.0015219476,0.0010531738,0.0013685778,0.0047215745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026348425,0.0001528516,0.33410627,0.0009487329,0.0002816672,0.0005214735,0.005077787,0.002329371,0.0011387228,0.0061468887,0.56006837,0.08896433],"study_design_scores_gemma":[0.000039046135,0.00018189641,0.633692,0.001816803,0.00033662101,0.00045026792,0.027852425,0.0054448787,0.002456029,0.002997148,0.32455873,0.00017419057],"about_ca_topic_score_codex":0.42949748,"about_ca_topic_score_gemma":0.5401702,"teacher_disagreement_score":0.42949748,"about_ca_system_score_codex":0.0014841803,"about_ca_system_score_gemma":0.0026674555,"threshold_uncertainty_score":0.8539951},"labels":[],"label_agreement":null},{"id":"W2518238244","doi":"10.1177/1354816616662761","title":"Human resource management impacts on labour productivity in tourism","year":2016,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Hospitality and Tourism Education","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Industry, Tourism and Investment; University of Guelph","funders":"","keywords":"Productivity; Tourism; Estimation; Economics; Human capital; Labour economics; Econometric model; Human resource management; Resource (disambiguation); Immigration; Business; Econometrics; Geography; Economic growth","score_opus":0.013102825086654286,"score_gpt":0.22211330930484052,"score_spread":0.20901048421818624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2518238244","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98991513,0.00027967233,0.00027634815,0.0002606997,0.000009835456,0.000020736687,0.0007375935,0.0000134446545,0.008486605],"genre_scores_gemma":[0.998367,0.00010806909,0.000061373416,0.000012256318,0.00000616411,0.000004286706,0.00023309865,0.000002487601,0.00120525],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99896586,0.00023524428,0.000037449427,0.000052021747,0.000303471,0.0004060418],"domain_scores_gemma":[0.9975746,0.00047398632,0.000586733,0.000092914226,0.000636555,0.0006350897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009721177,0.00023736717,0.00020107394,0.0016380706,0.00081696536,0.0016368787,0.00029797494,0.00018076075,0.003378895],"category_scores_gemma":[0.0041113445,0.00009023925,0.0003600329,0.0029150834,0.00055772165,0.0004284843,0.0009534291,0.00037572396,0.00039332555],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014394578,0.00016270007,0.9581152,0.000044806147,0.00010323458,0.00028092516,0.0005469879,0.0061774873,0.00047126896,0.0012353684,0.001067541,0.03165051],"study_design_scores_gemma":[9.950177e-7,0.000024783116,0.9976432,0.000006211303,0.0000057845596,0.00001658437,0.00058278523,0.0008070292,0.00005828775,0.00014521836,0.00070494466,0.000004280658],"about_ca_topic_score_codex":0.2986845,"about_ca_topic_score_gemma":0.34427813,"teacher_disagreement_score":0.2986845,"about_ca_system_score_codex":0.0040231813,"about_ca_system_score_gemma":0.0039902725,"threshold_uncertainty_score":0.593892},"labels":[],"label_agreement":null},{"id":"W2586447965","doi":"10.1177/1354816616656273","title":"How to quantify and characterize day trippers at the local level","year":2017,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Sharing Economy and Platforms","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo","keywords":"Tourism; TRIPS architecture; Phenomenon; Relevance (law); Work (physics); Order (exchange); Regional science; Geography; Computer science; Operations research; Business; Transport engineering; Political science; Engineering","score_opus":0.05982842784600682,"score_gpt":0.22339989663812418,"score_spread":0.16357146879211737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586447965","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11623395,0.0014615079,0.85528857,0.0012273081,0.0001579591,0.00055440876,0.0034955554,0.00048010357,0.021100648],"genre_scores_gemma":[0.5322484,0.0010463613,0.4589049,0.00019524037,0.00010270073,0.00062475394,0.002423943,0.00021253456,0.004241115],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99725276,0.00093419617,0.00028408266,0.00073903607,0.0005772709,0.0002125426],"domain_scores_gemma":[0.99497,0.0013599594,0.001158069,0.0008313934,0.0014590191,0.00022157132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027523297,0.00081074645,0.0007411117,0.0036939797,0.000776717,0.0041870666,0.0011433228,0.00070264604,0.0027221995],"category_scores_gemma":[0.009045386,0.0002993511,0.00064690824,0.0036358174,0.0010988007,0.0042489544,0.0017685529,0.0008777676,0.0015973458],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014967646,0.0001885333,0.20001379,0.0017550895,0.0005833456,0.00036012853,0.008962693,0.038341846,0.011481717,0.16220096,0.01624268,0.55971956],"study_design_scores_gemma":[0.000035026987,0.00044265809,0.33859503,0.0016915184,0.00032177015,0.0018071638,0.039155465,0.12564284,0.015915655,0.2619769,0.21386304,0.0005528568],"about_ca_topic_score_codex":0.009452813,"about_ca_topic_score_gemma":0.008527031,"teacher_disagreement_score":0.009452813,"about_ca_system_score_codex":0.0010631421,"about_ca_system_score_gemma":0.0014617159,"threshold_uncertainty_score":0.01879561},"labels":[],"label_agreement":null},{"id":"W2899119869","doi":"10.1177/1354816618806729","title":"Sustainable tourism modeling: Pricing decisions and evolutionarily stable strategies for competitive tour operators","year":2018,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"Government of Jiangsu Province; National Natural Science Foundation of China","keywords":"Tourism; Competitive advantage; Disadvantage; Subsidy; Government (linguistics); Business; Product (mathematics); Industrial organization; Pricing strategies; Marketing; Preference; Economics; Sustainable development; Microeconomics; Computer science; Ecology; Market economy","score_opus":0.03960422984212527,"score_gpt":0.3145504998467476,"score_spread":0.27494627000462235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899119869","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6122787,0.0005185816,0.34309408,0.0032347182,0.00010959041,0.00017553194,0.0002257689,0.00006571885,0.040297344],"genre_scores_gemma":[0.98051363,0.00023141177,0.01144575,0.00010897239,0.000025392534,0.00011801763,0.0000516545,0.000011573159,0.0074936347],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995179,0.00027186246,0.000014475338,0.000071807626,0.000043084186,0.00008089911],"domain_scores_gemma":[0.9986426,0.0008279996,0.00021952174,0.00004382888,0.00010092391,0.00016513122],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012873778,0.00097654806,0.00070542574,0.0006558148,0.0006572492,0.0019441812,0.0012696523,0.002450616,0.0047442564],"category_scores_gemma":[0.0046784994,0.00041000085,0.0009267786,0.0004985304,0.0013231252,0.0017868589,0.0009880866,0.0015253338,0.00030410782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084653555,0.0001529887,0.0048657237,0.000051456405,0.000073064446,0.00029627612,0.0002828378,0.8008506,0.00091870676,0.18600357,0.0009032707,0.005516853],"study_design_scores_gemma":[0.000014905601,0.000035003835,0.00048613592,0.0000059245504,0.000010860605,0.000020208961,0.00009046185,0.9750963,0.00004227817,0.02381841,0.00036945374,0.000010130883],"about_ca_topic_score_codex":0.011254559,"about_ca_topic_score_gemma":0.008103195,"teacher_disagreement_score":0.011254559,"about_ca_system_score_codex":0.0016447563,"about_ca_system_score_gemma":0.0011798318,"threshold_uncertainty_score":0.022378087},"labels":[],"label_agreement":null},{"id":"W2945207185","doi":"10.1177/1354816619851404","title":"Armed conflict, military expenditure and international tourism","year":2019,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Defense, Military, and Policy Studies","field":"Economics, Econometrics and Finance","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Algoma University","funders":"","keywords":"Tourism; Attractiveness; Panel data; Armed conflict; Middle East; Economics; Development economics; International trade; Geography; Political science","score_opus":0.02825933184815261,"score_gpt":0.23003633298338438,"score_spread":0.20177700113523178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945207185","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98542225,0.0022002978,0.001527182,0.0013763205,0.0000506206,0.000028752505,0.0021351252,0.000054211523,0.0072052577],"genre_scores_gemma":[0.99650335,0.00070324633,0.00017769536,0.000062214924,0.000022771917,0.000014923197,0.0010705069,0.000004808617,0.001440528],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99945813,0.00020917786,0.000030860265,0.000060131002,0.000052873915,0.00018885032],"domain_scores_gemma":[0.99758935,0.0008671566,0.00090056495,0.0001132793,0.000098076576,0.0004314925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006164599,0.0005049187,0.0005771591,0.0016299458,0.0004183737,0.0016682817,0.0004057136,0.00068864773,0.007222198],"category_scores_gemma":[0.0026251138,0.0002573733,0.001142719,0.0027643458,0.00086377363,0.0007615065,0.0015077572,0.0012783781,0.0006459967],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025348863,0.00021477693,0.9370106,0.0001167733,0.0010095349,0.00053361634,0.0002611367,0.03641433,0.00026020547,0.012310563,0.0031699182,0.008445026],"study_design_scores_gemma":[0.00011056775,0.00055418955,0.92522407,0.00019266557,0.00063496054,0.0003923352,0.0021249596,0.0465966,0.0003152027,0.010526133,0.01324485,0.000083555125],"about_ca_topic_score_codex":0.04333599,"about_ca_topic_score_gemma":0.029295744,"teacher_disagreement_score":0.04333599,"about_ca_system_score_codex":0.0011726643,"about_ca_system_score_gemma":0.0010157499,"threshold_uncertainty_score":0.086167455},"labels":[],"label_agreement":null},{"id":"W2991267448","doi":"10.1177/1354816619888346","title":"Testing the efficacy of the economic policy uncertainty index on tourism demand in USMCA: Theory and evidence","year":2019,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":254,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Index (typography); Economics; Economic impact analysis; Explanatory power; Economic policy; Public economics; Political science; Microeconomics","score_opus":0.02489465364976254,"score_gpt":0.23824202617551724,"score_spread":0.2133473725257547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991267448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9902255,0.002019273,0.0010831694,0.0013625327,0.00006276524,0.00005650415,0.0012665616,0.00001597402,0.0039076665],"genre_scores_gemma":[0.9976326,0.0006325482,0.00038255542,0.000120556484,0.00004440396,0.000021228121,0.0009434069,0.0000058040155,0.00021688272],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99482733,0.0027923123,0.0003238816,0.0008289183,0.0008446552,0.00038291616],"domain_scores_gemma":[0.894455,0.083381794,0.010748557,0.0032322735,0.0066193137,0.0015630149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0110894395,0.0007918831,0.00061888946,0.001975965,0.0008636955,0.0021198017,0.0019111843,0.0010752758,0.0035656556],"category_scores_gemma":[0.047687374,0.00050374545,0.0019211447,0.002414585,0.0017548683,0.0019815727,0.0021021152,0.0018369263,0.0006400979],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027825875,0.00035137148,0.987323,0.000115300776,0.0011113698,0.00006388498,0.00033337084,0.0012788158,0.000034712073,0.0010212584,0.0006974145,0.007391361],"study_design_scores_gemma":[0.00008477568,0.0007990124,0.95579225,0.000397477,0.0021243277,0.00009228864,0.0037609925,0.03036409,0.00044981818,0.00203648,0.00404741,0.00005099916],"about_ca_topic_score_codex":0.10335733,"about_ca_topic_score_gemma":0.056143902,"teacher_disagreement_score":0.10335733,"about_ca_system_score_codex":0.0017830441,"about_ca_system_score_gemma":0.002026441,"threshold_uncertainty_score":0.20551139},"labels":[],"label_agreement":null},{"id":"W3123446556","doi":"10.1177/1354816620985382","title":"Economic policy uncertainty, consumer confidence in major economies and outbound tourism to African countries","year":2021,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Consumer confidence index; Economics; China; Panel data; Economic impact analysis; Brexit; Development economics; Economy; International economics; Macroeconomics; Geography; European union; Econometrics","score_opus":0.014181139325394927,"score_gpt":0.23222296125571543,"score_spread":0.2180418219303205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123446556","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984633,0.0001946038,0.00003776973,0.00028808313,0.0000032188113,0.0000020085931,0.000113018395,7.067365e-7,0.0008973168],"genre_scores_gemma":[0.999683,0.00012011568,0.00001215045,0.0000139789745,0.0000025648023,0.0000011308535,0.0000630429,3.6770243e-7,0.000103540566],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973756,0.00009238153,0.00001851672,0.000024220286,0.00003872107,0.000088587534],"domain_scores_gemma":[0.9973918,0.000792434,0.0012350823,0.00006986076,0.00021367343,0.00029706387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005616016,0.00010837585,0.00020225745,0.0006256868,0.0004522333,0.00128518,0.0001343019,0.00029578307,0.0013221294],"category_scores_gemma":[0.004149395,0.000083355386,0.00025750458,0.0012256083,0.0004174624,0.00067947886,0.0008563151,0.0008070197,0.00006917973],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012123346,0.000065303255,0.9888053,0.000034057863,0.00006675778,0.00038655492,0.0014846794,0.002247769,0.00012353393,0.0011663935,0.00050381303,0.0049946276],"study_design_scores_gemma":[0.0000027496624,0.000030601874,0.99038106,0.000040929684,0.000020240283,0.00006886492,0.0059708534,0.002107142,0.00012228392,0.00035669372,0.0008898131,0.00000874663],"about_ca_topic_score_codex":0.0413636,"about_ca_topic_score_gemma":0.04194042,"teacher_disagreement_score":0.0413636,"about_ca_system_score_codex":0.0009034692,"about_ca_system_score_gemma":0.00054989493,"threshold_uncertainty_score":0.08224565},"labels":[],"label_agreement":null},{"id":"W3136893022","doi":"10.1177/13548166211001589","title":"Challenge or chance? Understanding the impact of anti-corruption campaign on China’s hotel industry","year":2021,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Microfinance and Financial Inclusion","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Language change; China; Tourism; Quarter (Canadian coin); Business; Position (finance); Hotel industry; Entertainment; Marketing; Hospitality industry; Economics; Advertising; Political science; Finance","score_opus":0.08903439726926132,"score_gpt":0.2736907904319869,"score_spread":0.18465639316272559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136893022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958378,0.00019618323,0.0000756838,0.0006856087,0.0000060859675,0.0000061817836,0.00006128756,0.0000015173779,0.0031296418],"genre_scores_gemma":[0.99957377,0.00008543065,0.000011831752,0.000039178485,0.000006611905,0.0000024098879,0.000028042678,4.7876836e-7,0.0002522193],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995005,0.0001137744,0.000018339522,0.00005325257,0.000080170386,0.0002339266],"domain_scores_gemma":[0.99674207,0.000772008,0.0014338738,0.0001150949,0.00029455667,0.00064237346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007374904,0.0001724398,0.00029238244,0.0010725248,0.0006040026,0.0012638043,0.000252844,0.00034991832,0.003574243],"category_scores_gemma":[0.002297949,0.00010255262,0.00034375096,0.0008773592,0.0010420558,0.0011116903,0.00087157864,0.0006371004,0.00019599586],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035694873,0.000101961894,0.98712975,0.000031407595,0.000042215284,0.00016643576,0.0011814237,0.0010019734,0.00022818471,0.0023318285,0.00051985163,0.007229261],"study_design_scores_gemma":[0.0000025653546,0.000035185854,0.99460185,0.000017581564,0.000015831927,0.000009974412,0.0020561914,0.0020940774,0.00008627769,0.00046383892,0.0006108857,0.0000058233636],"about_ca_topic_score_codex":0.06755458,"about_ca_topic_score_gemma":0.08248268,"teacher_disagreement_score":0.06755458,"about_ca_system_score_codex":0.0021051331,"about_ca_system_score_gemma":0.0019060957,"threshold_uncertainty_score":0.13432276},"labels":[],"label_agreement":null},{"id":"W3173760208","doi":"10.1177/13548166211010659","title":"Business cycles and tourism imports in the South Pacific","year":2021,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Quarter (Canadian coin); Business cycle; Economics; Business; Economy; Economic geography; Geography; Macroeconomics","score_opus":0.02588834490933515,"score_gpt":0.27761148555790854,"score_spread":0.2517231406485734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3173760208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971169,0.00010208736,0.00004955599,0.00019250122,0.0000023652933,0.0000025144584,0.00013340046,0.0000018830573,0.0023988637],"genre_scores_gemma":[0.99890614,0.00016624926,0.000023773797,0.000013137906,0.0000040581735,0.0000018895727,0.0001817342,0.0000018195027,0.00070114946],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99988425,0.000019713816,0.000009392517,0.000019892948,0.00003947807,0.000027311335],"domain_scores_gemma":[0.9982333,0.00033515014,0.0009078495,0.000057811936,0.0001773821,0.00028846593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023912238,0.00009651394,0.00015355083,0.0006819255,0.00031642604,0.0011922051,0.00016285376,0.00017667994,0.0025384414],"category_scores_gemma":[0.0026224535,0.00010887843,0.000219652,0.0014830375,0.00055747264,0.00057965895,0.0006698013,0.0005144248,0.0001472136],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065497305,0.00003722345,0.9893433,0.00002143256,0.00005311322,0.00030446897,0.001632319,0.001021806,0.00023727109,0.0011835146,0.0004628272,0.0056372606],"study_design_scores_gemma":[0.000002170577,0.000014285153,0.9958871,0.000011898427,0.000010453864,0.000050101942,0.0015554035,0.0012955277,0.000050738523,0.00022775847,0.0008892834,0.0000051573847],"about_ca_topic_score_codex":0.1375656,"about_ca_topic_score_gemma":0.12834069,"teacher_disagreement_score":0.1375656,"about_ca_system_score_codex":0.001089622,"about_ca_system_score_gemma":0.0008215776,"threshold_uncertainty_score":0.27352977},"labels":[],"label_agreement":null},{"id":"W3175087940","doi":"10.1177/13548166211027844","title":"The impact of the COVID-19 pandemic on revenues of visitor attractions: An exploratory and preliminary study in China","year":2021,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Visitor pattern; Revenue; Tourism; Business; Renminbi; Economic impact analysis; China; Coronavirus disease 2019 (COVID-19); Estimation; Destinations; Marketing; Pandemic; Quarter (Canadian coin); Economics; Finance; Geography","score_opus":0.07415239827567824,"score_gpt":0.39155553362605966,"score_spread":0.31740313535038145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175087940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99928015,0.00003487086,0.000033205633,0.00004621102,0.000001445732,0.0000137767,0.000109191315,0.0000011067466,0.00048012554],"genre_scores_gemma":[0.9993137,0.00008888561,0.00004691663,0.000020033785,0.000002994867,0.000011616913,0.00013779588,7.3858604e-7,0.00037730573],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996588,0.00007283443,0.000021130796,0.000041336676,0.00006650975,0.00013947285],"domain_scores_gemma":[0.9992986,0.00011848213,0.000204909,0.000040362287,0.00017919551,0.00015851879],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071751646,0.00029708337,0.00024105552,0.0010857136,0.00082740915,0.0007179063,0.0004425046,0.00031449762,0.0014158572],"category_scores_gemma":[0.0009010453,0.00015545894,0.0004322883,0.0012202366,0.0005196676,0.00058890396,0.00084702566,0.0003497224,0.00013585188],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009330257,0.00017709669,0.9824652,0.000077328055,0.000045926427,0.0012469504,0.0033718897,0.0008899127,0.00065663905,0.00037281367,0.0006089711,0.00999399],"study_design_scores_gemma":[0.0000025431582,0.00012480536,0.99182737,0.000013689728,0.000012533177,0.00009268858,0.0061719064,0.001080716,0.0000918683,0.000045717454,0.0005257931,0.000010343802],"about_ca_topic_score_codex":0.12723237,"about_ca_topic_score_gemma":0.17272642,"teacher_disagreement_score":0.12723237,"about_ca_system_score_codex":0.0021720002,"about_ca_system_score_gemma":0.0019780293,"threshold_uncertainty_score":0.25298357},"labels":[],"label_agreement":null},{"id":"W3193798607","doi":"10.1177/13548166211035569","title":"Forecasting hotel room demand amid COVID-19","year":2021,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Hong Kong Polytechnic University","keywords":"Baseline (sea); Coronavirus disease 2019 (COVID-19); Quarter (Canadian coin); Pandemic; Tourism; Business; Distributed lag; Resilience (materials science); Index (typography); Duration (music); Economics; Econometrics; Geography; Computer science","score_opus":0.08252048935686428,"score_gpt":0.33347138749308536,"score_spread":0.25095089813622107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193798607","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99661994,0.000023265824,0.001389904,0.00014474148,0.000010996686,0.000015323998,0.0008871968,0.000029913681,0.0008787408],"genre_scores_gemma":[0.9984378,0.000026491487,0.00055908336,0.000007459793,0.0000029480102,0.0000061441924,0.00076678285,0.0000027907204,0.00019043026],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99986386,0.000033644515,0.000008123002,0.000028907729,0.000023020319,0.00004249603],"domain_scores_gemma":[0.9994923,0.00018085903,0.00007037565,0.000042973024,0.00013334208,0.000080075435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005237507,0.00036497676,0.0002467019,0.00030037743,0.00019334548,0.0005938219,0.0004058863,0.00060054986,0.0007605188],"category_scores_gemma":[0.0014774153,0.00018443323,0.00036818717,0.00029865553,0.0002240151,0.0005673998,0.00034363547,0.0005228524,0.0001589501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004985158,0.00013278694,0.10253773,0.00005056769,0.00006249614,0.0004068969,0.00015989371,0.88365483,0.002306193,0.0018523152,0.0021118617,0.006225914],"study_design_scores_gemma":[0.000013009242,0.000113670576,0.053116206,0.000006908491,0.000010916793,0.000019360603,0.00042565897,0.944719,0.00073294365,0.00034274004,0.00047766522,0.000021809123],"about_ca_topic_score_codex":0.060340483,"about_ca_topic_score_gemma":0.042931877,"teacher_disagreement_score":0.060340483,"about_ca_system_score_codex":0.0011535545,"about_ca_system_score_gemma":0.0006930392,"threshold_uncertainty_score":0.11997855},"labels":[],"label_agreement":null},{"id":"W3195006317","doi":"10.1177/13548166211029053","title":"Hosting annual international sporting events and tourism: Formula 1, golf or tennis?","year":2021,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Sport and Mega-Event Impacts","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Attractiveness; Tourism; Business; Advertising; Economic impact analysis; Marketing; Political science; Economics","score_opus":0.027524535357186738,"score_gpt":0.3039776575163591,"score_spread":0.27645312215917234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195006317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9560004,0.0020871616,0.0003225544,0.0060214736,0.00015692993,0.000048282607,0.0041842777,0.000027992692,0.031151008],"genre_scores_gemma":[0.9901939,0.0012991241,0.0003099697,0.00034406688,0.00008849313,0.000014497945,0.0020933724,0.000009882574,0.00564671],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99973446,0.000046555582,0.0000118230055,0.000026023923,0.000096430274,0.00008472215],"domain_scores_gemma":[0.9988605,0.00021457825,0.00054149487,0.000023552375,0.00013401825,0.00022578376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000324438,0.00015529923,0.00022342958,0.0005810465,0.0003384623,0.0016089819,0.00024008118,0.00032263485,0.008574793],"category_scores_gemma":[0.002552041,0.000068265275,0.00033081693,0.0012612406,0.00038994235,0.00082792214,0.0006491474,0.00087790063,0.0005079492],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024133976,0.00016784978,0.9173121,0.000268663,0.00011919837,0.0002461453,0.00068838167,0.0012695622,0.00021613349,0.005116633,0.024324005,0.05003003],"study_design_scores_gemma":[0.000010210734,0.000103368264,0.9781702,0.000110602545,0.00006463724,0.00005861354,0.0031192657,0.0008037219,0.00011013752,0.00044962918,0.016987799,0.000011888977],"about_ca_topic_score_codex":0.095260926,"about_ca_topic_score_gemma":0.17824702,"teacher_disagreement_score":0.095260926,"about_ca_system_score_codex":0.0013601157,"about_ca_system_score_gemma":0.00083397183,"threshold_uncertainty_score":0.18941289},"labels":[],"label_agreement":null},{"id":"W4280612044","doi":"10.1177/13548166221098320","title":"Stronger together: International tourists “spillover” into close countries","year":2022,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Spillover effect; Tourism; Contiguity; Economic geography; Distance decay; Spatial econometrics; Lag; Geographical distance; Geography; Spatial analysis; Econometrics; Economics; Computer science; Sociology; Macroeconomics","score_opus":0.01433078047097585,"score_gpt":0.29652366679139874,"score_spread":0.2821928863204229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280612044","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96446246,0.000853859,0.0025697444,0.00073205936,0.000043076445,0.00003571585,0.0006849437,0.000036760717,0.03058138],"genre_scores_gemma":[0.9977837,0.00038953684,0.00039855088,0.00007355833,0.000024496128,0.000010311599,0.00021690605,0.000004502673,0.0010984505],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948186,0.00016457385,0.000032567586,0.00010971664,0.000092428476,0.00011890483],"domain_scores_gemma":[0.9971727,0.0009317114,0.0010554226,0.00027748285,0.00026438283,0.00029826764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006692956,0.00024457302,0.0003716275,0.0015754355,0.0006660316,0.001729304,0.00025542008,0.00033830118,0.009754428],"category_scores_gemma":[0.004555502,0.00016329816,0.0006349074,0.0020943976,0.000927555,0.0015070445,0.0031046073,0.0006592473,0.0005773594],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022316595,0.00015036805,0.9172184,0.00034739668,0.0006446224,0.0011206276,0.007571451,0.004197419,0.0010700122,0.014240248,0.004003577,0.049212664],"study_design_scores_gemma":[0.0000122836045,0.0001120481,0.9741634,0.00015333896,0.00025294247,0.0002851513,0.011040896,0.0013895766,0.0003720269,0.0032603536,0.0089308275,0.000027212736],"about_ca_topic_score_codex":0.013949531,"about_ca_topic_score_gemma":0.021395015,"teacher_disagreement_score":0.013949531,"about_ca_system_score_codex":0.000686989,"about_ca_system_score_gemma":0.00047979434,"threshold_uncertainty_score":0.032631755},"labels":[],"label_agreement":null},{"id":"W4281389069","doi":"10.1177/13548166221104390","title":"Psychological factors of Canadian and Mexican tourists and the US tourism sector","year":2022,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tourism; Spillover effect; Vector autoregression; Terrorism; Natural disaster; Financial crisis; Business; Economics; Demographic economics; Development economics; Economy; Geography; Monetary economics; Macroeconomics","score_opus":0.037161464732356916,"score_gpt":0.28741443496245106,"score_spread":0.25025297023009413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281389069","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995282,0.00027021687,0.000028508639,0.000317836,0.000007851712,0.00000676847,0.00082379073,0.0000021533317,0.0032609007],"genre_scores_gemma":[0.9981464,0.00030127668,0.00003393904,0.000039462182,0.000006113815,0.0000026158552,0.00069060293,0.0000012380227,0.00077843346],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997656,0.000022639055,0.0000094897705,0.000023831448,0.00007175374,0.00010664656],"domain_scores_gemma":[0.9987925,0.00008703533,0.00045159686,0.000037313384,0.0002614824,0.00037003067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000297335,0.00016454876,0.00013458174,0.0010865829,0.0010475996,0.001283943,0.00019224014,0.00022856485,0.0020069487],"category_scores_gemma":[0.0016179712,0.00007911714,0.00030559007,0.0018689459,0.00043425034,0.00027310828,0.000559927,0.0005199849,0.00010530638],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055801265,0.000018432549,0.9940493,0.0000107888645,0.00003314042,0.000070384114,0.00070908177,0.00015089536,0.00012039976,0.0002609198,0.00082863815,0.0036920905],"study_design_scores_gemma":[5.759316e-7,0.0000034295222,0.9977921,0.0000046200435,0.0000060499947,0.000011660936,0.0014500926,0.00006356387,0.000013083739,0.000009207667,0.00064250675,0.0000030412116],"about_ca_topic_score_codex":0.93278515,"about_ca_topic_score_gemma":0.963255,"teacher_disagreement_score":0.06721485,"about_ca_system_score_codex":0.004855493,"about_ca_system_score_gemma":0.0046507465,"threshold_uncertainty_score":0.1352213},"labels":[],"label_agreement":null},{"id":"W4402335750","doi":"10.1177/13548166241280404","title":"Gamification and economic behavior: Geospatial insights into mobile exercise app usage in South Korea","year":2024,"lang":"en","type":"article","venue":"Tourism Economics","topic":"Educational Games and Gamification","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Geospatial analysis; Mobile apps; Tourism; Business; Marketing; Advertising; Computer science; Geography; World Wide Web; Remote sensing","score_opus":0.013475753276900315,"score_gpt":0.279479515628763,"score_spread":0.2660037623518627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402335750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99841344,0.00009480412,0.0003791521,0.00008716167,0.0000018106396,0.000007161669,0.00014791095,0.000006349609,0.00086232345],"genre_scores_gemma":[0.9992865,0.00010135572,0.00036182726,0.000013751388,7.4270423e-7,0.0000069431253,0.00010368492,0.0000027177746,0.00012258513],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99970955,0.00012626391,0.000023369019,0.000057939353,0.000033093227,0.00004974377],"domain_scores_gemma":[0.9992926,0.0002841739,0.00021778543,0.000048723126,0.00007766771,0.00007897864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044632092,0.00031713667,0.00022307325,0.0014572074,0.0003125714,0.0011334395,0.00023551389,0.00022996735,0.0014865672],"category_scores_gemma":[0.001704032,0.00018046626,0.0003930692,0.0020331242,0.00045299286,0.0012309022,0.0013245525,0.0003961843,0.00015482167],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012532776,0.0001925509,0.9615604,0.00011045621,0.00009489938,0.0004961208,0.006846378,0.0012355883,0.00075070694,0.00096691714,0.00039790582,0.027222825],"study_design_scores_gemma":[0.0000053167378,0.00007939535,0.96759385,0.000082509534,0.00006525137,0.00021981151,0.024731275,0.0043024183,0.00019407808,0.0010333048,0.0016666694,0.000026257248],"about_ca_topic_score_codex":0.012935964,"about_ca_topic_score_gemma":0.034038246,"teacher_disagreement_score":0.012935964,"about_ca_system_score_codex":0.00039019316,"about_ca_system_score_gemma":0.00045928312,"threshold_uncertainty_score":0.025721312},"labels":[],"label_agreement":null}]}