{"meta":{"query_hash":"b6f8ef980604","filters":{"venue":"Review of Regional Research"},"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/b6f8ef980604","api":"https://metacan.xera.ac/api/v1/cohort?venue=Review+of+Regional+Research"},"results":[{"id":"W1569066934","doi":"10.1007/s10037-013-0083-8","title":"Forecasting gross value-added at the regional level: are sectoral disaggregated predictions superior to direct ones?","year":2014,"lang":"en","type":"article","venue":"Review of Regional Research","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pooling; Autoregressive model; Econometrics; Gross value added; Distributed lag; Economics; Quarter (Canadian coin); Lag; Value (mathematics); Mathematics; Statistics; Geography; Economy; Computer science","score_opus":0.46977946718223484,"score_gpt":0.36820063122742136,"score_spread":0.10157883595481348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1569066934","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8017236,0.11202937,0.000530616,0.062177654,0.0004949244,0.0024409343,0.0013809141,0.000075395095,0.019146582],"genre_scores_gemma":[0.96380794,0.024580514,0.00034381778,0.002728123,0.0006830665,0.00019767866,0.00012718885,0.00006123313,0.00747043],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99742573,0.0002513954,0.000855519,0.00055063865,0.00024079518,0.0006759307],"domain_scores_gemma":[0.99765396,0.00088122004,0.00036450574,0.00071149244,0.00011745971,0.00027138324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046103285,0.00020955066,0.00071299175,0.00027394987,0.0005069111,0.00005435127,0.00058059726,0.00009525831,0.00078686955],"category_scores_gemma":[0.0020013512,0.00017242976,0.00032877087,0.000648794,0.00033028284,0.00019471979,0.000239768,0.00035475352,0.0007437366],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000414784,0.0003840704,0.0728731,0.0068923114,0.00057965296,0.000012089885,0.0012428056,0.004556399,0.000061536426,0.06592176,0.8351604,0.011901104],"study_design_scores_gemma":[0.0004654573,0.00023268268,0.05110008,0.0033894628,0.000015815893,0.000053781627,0.000045051733,0.01634715,0.000026329624,0.0026415691,0.92534727,0.00033536216],"about_ca_topic_score_codex":0.0012875346,"about_ca_topic_score_gemma":0.00018519379,"teacher_disagreement_score":0.16208434,"about_ca_system_score_codex":0.0003119742,"about_ca_system_score_gemma":0.000060611877,"threshold_uncertainty_score":0.9559477},"labels":[],"label_agreement":null},{"id":"W2031189329","doi":"10.1007/s10037-007-0018-3","title":"The Interregional and Intertemporal Allocation of EU Producer Support: Magnitude and Determinants","year":2007,"lang":"en","type":"article","venue":"Review of Regional Research","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Common Agricultural Policy; Economics; European union; Distribution (mathematics); Cohesion (chemistry); Agriculture; Diversity (politics); Empirical evidence; Causality (physics); German; Empirical research; Economic geography; Geography; International trade; Political science; Statistics","score_opus":0.10776284025547225,"score_gpt":0.3915041771796821,"score_spread":0.2837413369242099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031189329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9644721,0.019932648,1.7586866e-7,0.014600727,0.000017899521,0.00028466733,0.000006030358,0.0000023607129,0.00068339],"genre_scores_gemma":[0.91419137,0.08505378,0.000023398576,0.0002253758,0.0000993385,0.0000075039707,0.000013097362,5.382019e-7,0.00038560358],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99908066,0.00007912241,0.00029021248,0.00015030504,0.00021750774,0.00018219413],"domain_scores_gemma":[0.99902433,0.00049257337,0.00011820278,0.000046608948,0.00024393825,0.00007437317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020827143,0.000064027874,0.00015482494,0.000012901559,0.00010620587,0.000014981841,0.00017546398,0.000032203472,0.000029657096],"category_scores_gemma":[0.00017386684,0.000019018104,0.000045411358,0.00014764299,0.00032603327,0.000060954746,0.00012191655,0.00010183967,0.0000036541119],"study_design_candidate":"design_other","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":[0.000072289615,0.00005133244,0.009142551,0.0009068874,0.000018081251,0.0000019595798,0.00008805417,1.0540999e-8,0.008304887,0.008264622,0.0132609,0.9598884],"study_design_scores_gemma":[0.000102109196,0.0005161853,0.50897735,0.0018937901,0.000008783174,0.00008282342,0.0002727355,0.000010330733,0.0011995086,0.000914406,0.4859025,0.000119503806],"about_ca_topic_score_codex":0.00017783641,"about_ca_topic_score_gemma":0.0004424295,"teacher_disagreement_score":0.95976895,"about_ca_system_score_codex":0.000012817248,"about_ca_system_score_gemma":0.000019030338,"threshold_uncertainty_score":0.12012832},"labels":[],"label_agreement":null},{"id":"W4311974426","doi":"10.1007/s10037-022-00175-0","title":"Asian female migrant aged care workers in regional Australia and social resilience","year":2022,"lang":"en","type":"article","venue":"Review of Regional Research","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"La Trobe University","keywords":"Narrative; Psychological resilience; Qualitative research; Gender studies; Coping (psychology); Sociology; Political science; Psychology; Social psychology; Social science","score_opus":0.33786661991645073,"score_gpt":0.5550921444565386,"score_spread":0.21722552454008792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311974426","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73085636,0.16353904,7.2536096e-7,0.09981335,0.00012571391,0.00228212,0.000046124555,0.000022341494,0.00331425],"genre_scores_gemma":[0.94553936,0.044835083,0.00007508654,0.0010183995,0.00019534296,0.00097025617,0.00008148908,0.00002416918,0.007260793],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99510455,0.0021980747,0.0004830992,0.00033098794,0.0013179075,0.00056539086],"domain_scores_gemma":[0.9986802,0.00061985484,0.00013843585,0.00019429368,0.00029048632,0.000076759025],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0032452145,0.00011719951,0.00039583864,0.00021346989,0.001562325,0.0000035280482,0.00031009558,0.00005960112,0.00050237525],"category_scores_gemma":[0.00022163751,0.00010209837,0.000098528224,0.00073438615,0.00039228762,0.000053956926,0.000473331,0.0011854684,0.000020848987],"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":[0.00021694084,0.00007992611,0.55031633,0.016676737,0.000033205833,0.000042391708,0.013351202,5.675273e-7,0.00003873342,0.0065995515,0.4062475,0.0063969046],"study_design_scores_gemma":[0.0004500873,0.000111646266,0.4269823,0.0053164144,0.000008650528,0.0000027894225,0.030022789,3.9845077e-7,5.991868e-7,0.00029626765,0.536701,0.0001069994],"about_ca_topic_score_codex":0.0017838576,"about_ca_topic_score_gemma":0.00090161565,"teacher_disagreement_score":0.21468304,"about_ca_system_score_codex":0.0002917724,"about_ca_system_score_gemma":0.00044946093,"threshold_uncertainty_score":0.9997375},"labels":[],"label_agreement":null},{"id":"W4376128954","doi":"10.1007/s10037-023-00186-5","title":"The US State-Level Geographic J-curve Hypothesis Mapping with Canada","year":2023,"lang":"en","type":"article","venue":"Review of Regional Research","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; State (computer science); Bilateral trade; Colored; Empirical evidence; Monetary economics; International economics; Econometrics; Geography; Political science","score_opus":0.3443676860932162,"score_gpt":0.30319783278359846,"score_spread":0.041169853309617754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376128954","genre_codex":"empirical","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50423354,0.40002963,0.00004453401,0.056115344,0.0003215387,0.0016098934,0.0009202107,0.000054069464,0.03667122],"genre_scores_gemma":[0.22564492,0.77024114,0.00018066184,0.0008402695,0.0000653298,0.00009805747,0.000026557282,0.000031742547,0.0028713234],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984049,0.00005925585,0.0005196238,0.00029344726,0.0001933824,0.0005293577],"domain_scores_gemma":[0.9984877,0.00063008175,0.00019864022,0.0004219411,0.00014955559,0.0001120907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030702488,0.00010830716,0.00036767038,0.00019198477,0.00025429894,0.000040054558,0.00051570975,0.00003099986,0.00005549238],"category_scores_gemma":[0.00045562166,0.0000831238,0.00010602923,0.0011526862,0.00019895483,0.00007370942,0.00008805146,0.00022649685,0.00028263143],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000829483,0.00008785767,0.2255799,0.00814713,0.00065691007,0.00007990142,0.00010582344,0.00016887735,0.000005058138,0.27817675,0.449427,0.03748181],"study_design_scores_gemma":[0.00011938356,0.000033088974,0.13910674,0.0008747329,0.000001943166,0.000006536748,0.000051432173,0.000100659636,0.0000028813918,0.009257931,0.85032564,0.000119031436],"about_ca_topic_score_codex":0.100900486,"about_ca_topic_score_gemma":0.06951148,"teacher_disagreement_score":0.40089864,"about_ca_system_score_codex":0.00015323368,"about_ca_system_score_gemma":0.00035397464,"threshold_uncertainty_score":0.9474675},"labels":[],"label_agreement":null}]}