{"meta":{"query_hash":"7241b2505f3d","filters":{"venue":"Geography and Geo-Information Science"},"cohort_total":4,"direct_labels_cover":0,"predictions_cover":4,"exported":4,"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/7241b2505f3d","api":"https://metacan.xera.ac/api/v1/cohort?venue=Geography+and+Geo-Information+Science"},"results":[{"id":"W2372094455","doi":"","title":"Tourism Complex and Tourism-Oriented Comprehensive Land Development:An Exploratory Research","year":2012,"lang":"en","type":"article","venue":"Geography and Geo-Information Science","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Tourism; Business; Tourism geography; Ecotourism; China; Land use; Transformative learning; Realm; Economic geography; Land development; Land management; Environmental planning; Environmental resource management; Regional science; Geography; Civil engineering; Economics; Sociology; Engineering","score_opus":0.08966277711833381,"score_gpt":0.37711217359569177,"score_spread":0.28744939647735795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2372094455","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":[0.9858175,0.0005157364,0.0012628406,0.0002542004,0.0000057738253,0.00021711127,0.00016856671,0.000004632546,0.011753765],"genre_scores_gemma":[0.9939604,0.0010765454,0.0017656194,0.000057444973,0.000010014048,0.0001839986,0.0001375919,0.000005072458,0.00280335],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.99934834,0.00040150515,0.000022698838,0.000055341985,0.0000772324,0.000094903306],"domain_scores_gemma":[0.9992454,0.00047402305,0.00008044052,0.000039267154,0.000065771965,0.00009519201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010434993,0.00028226865,0.00033525104,0.0016952036,0.0014129048,0.0023011412,0.00048417502,0.00042176002,0.0041984324],"category_scores_gemma":[0.0012066702,0.00019671686,0.0003878139,0.003084959,0.0016113296,0.0018083974,0.0017842097,0.00045704222,0.00029785308],"study_design_candidate":"qualitative","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":[0.0004724011,0.0026093032,0.45895964,0.0019722765,0.00018976378,0.008570917,0.34243208,0.002099031,0.004086334,0.07084208,0.00552752,0.102238655],"study_design_scores_gemma":[0.000036661513,0.0007109878,0.26087534,0.00036830196,0.00010128276,0.0020012842,0.6867516,0.0053809416,0.0008202061,0.0077479794,0.035163965,0.000041460098],"about_ca_topic_score_codex":0.004192233,"about_ca_topic_score_gemma":0.008249807,"teacher_disagreement_score":0.0041984324,"about_ca_system_score_codex":0.0012032888,"about_ca_system_score_gemma":0.00144515,"threshold_uncertainty_score":0.014045179},"labels":[],"label_agreement":null},{"id":"W2377280609","doi":"","title":"Database Model Based on Spatio-temporal Ontology","year":2010,"lang":"en","type":"article","venue":"Geography and Geo-Information Science","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Ontology; Computer science; Ontology-based data integration; Suggested Upper Merged Ontology; Semantics (computer science); Process ontology; Information retrieval; Upper ontology; Ontology Inference Layer; Tuple; Database; OWL-S; Semantic Web; Programming language; Semantic Web Stack; Mathematics","score_opus":0.010211255168305481,"score_gpt":0.27344020305677885,"score_spread":0.2632289478884734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2377280609","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":[0.010700464,0.0011365069,0.95550144,0.0017185505,0.0002349196,0.00029750622,0.0023609754,0.00123069,0.026818866],"genre_scores_gemma":[0.4472795,0.004460096,0.5100979,0.0008698229,0.00029177737,0.0011767356,0.0076216846,0.00018978088,0.028012794],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976578,0.0003747474,0.00042079008,0.000557994,0.0008474689,0.00014124425],"domain_scores_gemma":[0.9987092,0.000262311,0.00013566815,0.00031735547,0.00047995028,0.0000954552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016581567,0.00049508485,0.0007016172,0.0016147946,0.0010959014,0.0059256908,0.0033759691,0.0012720865,0.004293026],"category_scores_gemma":[0.002760401,0.0004181614,0.0014586749,0.0035939184,0.00087875425,0.009554065,0.0018721251,0.001423056,0.0015702134],"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":[0.000107474305,0.00007541963,0.0011003113,0.00024134443,0.00006523603,0.00059382984,0.0005958402,0.040967118,0.0023393768,0.90730774,0.007487212,0.039119184],"study_design_scores_gemma":[0.00012716612,0.00009502482,0.0006276772,0.00013093592,0.00017089011,0.0013190343,0.0005565464,0.544292,0.003513797,0.26701894,0.18207414,0.000073934854],"about_ca_topic_score_codex":0.015621432,"about_ca_topic_score_gemma":0.008632903,"teacher_disagreement_score":0.015621432,"about_ca_system_score_codex":0.002001574,"about_ca_system_score_gemma":0.0029887368,"threshold_uncertainty_score":0.031060994},"labels":[],"label_agreement":null},{"id":"W2382121264","doi":"","title":"Synthetic Evaluation of International Competitive Capability of 11 Biggest Countries in Tourism","year":2004,"lang":"en","type":"article","venue":"Geography and Geo-Information Science","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":0,"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; China; Competitive advantage; Business; Economy; International trade; Geography; Economics; Marketing","score_opus":0.011991792335265178,"score_gpt":0.23794325310848968,"score_spread":0.2259514607732245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2382121264","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":[0.98253644,0.00008855759,0.0013026395,0.000041982636,0.000009409692,0.000041548923,0.0008492688,0.0000150022815,0.015115314],"genre_scores_gemma":[0.9982805,0.000033568627,0.0005736886,0.000004850259,0.000003386062,0.000017418528,0.000801393,0.0000030446856,0.00028217427],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99864,0.000533309,0.00010318357,0.00008443978,0.00047000844,0.0001689921],"domain_scores_gemma":[0.9959616,0.0014272783,0.0006960837,0.0002283743,0.001186895,0.0004997744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018524377,0.00034559175,0.00027948045,0.0045175273,0.0006877977,0.0017654309,0.00022535444,0.00029105216,0.002524088],"category_scores_gemma":[0.0065008104,0.0000902229,0.00036061805,0.0039459052,0.0005339475,0.0014583576,0.0013724818,0.0003048428,0.00018771023],"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":[0.0018182421,0.00048272678,0.78413546,0.00055387645,0.00051582145,0.0009180362,0.002502958,0.0653929,0.0051775174,0.015971856,0.0037460092,0.11878475],"study_design_scores_gemma":[0.000048337577,0.0011379352,0.89638513,0.00010029485,0.00013277319,0.0006342403,0.012699526,0.067940116,0.004564573,0.0047788783,0.011459095,0.00011910195],"about_ca_topic_score_codex":0.0029613208,"about_ca_topic_score_gemma":0.003633034,"teacher_disagreement_score":0.0045175273,"about_ca_system_score_codex":0.0007491187,"about_ca_system_score_gemma":0.00035777656,"threshold_uncertainty_score":0.009796739},"labels":[],"label_agreement":null},{"id":"W2386341906","doi":"","title":"Study on Economic Factor Relation of Jiangsu Counties and Evolution Process Based on Quantile Regression","year":2013,"lang":"en","type":"article","venue":"Geography and Geo-Information Science","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Science North","funders":"","keywords":"Quantile regression; Econometrics; Quantile; Diversification (marketing strategy); Dilemma; Ordinary least squares; Regression; Regression analysis; Nonparametric statistics; Mathematics; Economics; Statistics","score_opus":0.01720145706857132,"score_gpt":0.22780561513475803,"score_spread":0.2106041580661867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2386341906","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":[0.98205113,0.00020640489,0.015869297,0.00020614934,0.000009380849,0.000013196495,0.00022112821,0.000041314648,0.0013819644],"genre_scores_gemma":[0.99860054,0.00007569614,0.00069789606,0.0000063059633,0.000005426208,0.0000050634094,0.00015510037,0.0000050661047,0.00044893046],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99960667,0.00013872127,0.000017428933,0.00010409658,0.000056274697,0.000076952],"domain_scores_gemma":[0.9988656,0.00057336496,0.00019541025,0.00009491012,0.00019838873,0.00007241545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010875247,0.0001769355,0.0002511516,0.0012855179,0.0002665282,0.0005586143,0.00038697245,0.00022401853,0.0019152883],"category_scores_gemma":[0.004134031,0.00014593672,0.0005575486,0.0015753208,0.00022013085,0.000748835,0.00037193196,0.00037814278,0.00011318515],"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":[0.000054284417,0.000049977727,0.926973,0.00004459986,0.00016487863,0.00037686946,0.0007114447,0.034313507,0.00059883227,0.011510362,0.00082946237,0.02437284],"study_design_scores_gemma":[0.000007704548,0.00004488962,0.6958705,0.000018681894,0.00010544219,0.00015246723,0.00061714405,0.29618737,0.0004656607,0.004557336,0.0019538002,0.000018977938],"about_ca_topic_score_codex":0.02905422,"about_ca_topic_score_gemma":0.015904317,"teacher_disagreement_score":0.02905422,"about_ca_system_score_codex":0.00059333566,"about_ca_system_score_gemma":0.00038737233,"threshold_uncertainty_score":0.057770193},"labels":[],"label_agreement":null}]}