{"meta":{"query_hash":"205fe33eabcc","filters":{"venue":"Regional Statistics"},"cohort_total":2,"direct_labels_cover":0,"predictions_cover":2,"exported":2,"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/205fe33eabcc","api":"https://metacan.xera.ac/api/v1/cohort?venue=Regional+Statistics"},"results":[{"id":"W3093479318","doi":"10.15196/rs100210","title":"National probabilities of the coronavirus spreading over time in Europe based on migration networks","year":2020,"lang":"en","type":"article","venue":"Regional Statistics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":32,"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":"Destinations; Mass migration; Economic geography; Geography; Human migration; Irregular migration; Vulnerability (computing); Coronavirus disease 2019 (COVID-19); Population; Pandemic; Development economics; Immigration; Demographic economics; Political science; Demography; Tourism; Sociology; Economics; Infectious disease (medical specialty)","score_opus":0.2794704273695275,"score_gpt":0.39495279830716024,"score_spread":0.11548237093763275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093479318","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25086614,0.00038168303,0.67056686,0.06452375,0.000433951,0.0036036612,0.0020821209,0.00033057455,0.0072112507],"genre_scores_gemma":[0.9742603,0.000028699602,0.01894463,0.006284063,0.00016220631,0.000030674117,0.000047800488,0.000023893655,0.00021776927],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986757,0.00021816867,0.0003628719,0.00018869541,0.0004129822,0.00014155405],"domain_scores_gemma":[0.9930588,0.00643581,0.00018813378,0.000100900135,0.00018017013,0.00003618752],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0003516386,0.00012091575,0.00023177968,0.000020047046,0.00006329425,0.000007884649,0.00014360911,0.000050610815,0.00008231664],"category_scores_gemma":[0.009810406,0.00008243381,0.000044470566,0.00026103968,0.00014909502,0.000024106967,0.000062021805,0.00015903106,0.000009856091],"study_design_candidate":"theoretical_or_conceptual","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":[0.00021267287,0.0002285067,0.043531705,0.00020139242,0.00003553135,0.000005756743,0.0003796453,0.103732266,0.00009297467,0.7481149,0.10287951,0.0005851757],"study_design_scores_gemma":[0.00042329158,0.00015029046,0.123098485,0.00012247152,0.000019713876,5.588594e-7,0.000012400399,0.7274973,0.000017119277,0.14088507,0.007605985,0.00016735648],"about_ca_topic_score_codex":0.000044348402,"about_ca_topic_score_gemma":0.000088857225,"teacher_disagreement_score":0.7233941,"about_ca_system_score_codex":0.000117698844,"about_ca_system_score_gemma":0.000092764705,"threshold_uncertainty_score":0.9985304},"labels":[],"label_agreement":null},{"id":"W4292481346","doi":"10.15196/rs120107","title":"Has COVID-19 caused a change in the dynamics of the unemployment rate? The case of North America and continental Europe","year":2022,"lang":"en","type":"article","venue":"Regional Statistics","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","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":"Coronavirus disease 2019 (COVID-19); Unemployment; Dynamics (music); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Geography; Economic geography; Economics; Sociology; Economic growth; Virology; Medicine; Outbreak","score_opus":0.10299351954724204,"score_gpt":0.28865935917348895,"score_spread":0.18566583962624691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292481346","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":[0.9526947,0.0006863586,0.0059043407,0.029360263,0.00018701433,0.0008519704,0.010213663,0.00000765022,0.00009405255],"genre_scores_gemma":[0.9936334,0.00017671083,0.000078443794,0.005887687,0.00002072589,0.000042735253,0.00007186015,0.000012492519,0.000075970675],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904656,0.00015078115,0.00039776455,0.00017094106,0.00007428394,0.00015968873],"domain_scores_gemma":[0.9983094,0.00087895006,0.00046138177,0.0002808531,0.0000247776,0.000044682645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048514587,0.00010054933,0.00021704666,0.00006968931,0.00023749044,0.0000188479,0.00028850135,0.000015283065,0.000056514542],"category_scores_gemma":[0.0004941533,0.00006884003,0.000038154925,0.0004373595,0.0003475954,0.000027494525,0.00018835615,0.00018623947,0.000001965852],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013680024,0.00036163282,0.5147819,0.00016036964,0.000108154985,0.0004333816,0.019650472,0.0034341263,0.0000039191223,0.44266436,0.015796764,0.0024681496],"study_design_scores_gemma":[0.0021918504,0.00038688284,0.61010677,0.00001452639,0.000051033672,0.00049166306,0.002423528,0.10169452,0.0000012191358,0.012228209,0.2700499,0.00035989715],"about_ca_topic_score_codex":0.009466473,"about_ca_topic_score_gemma":0.0065465407,"teacher_disagreement_score":0.43043616,"about_ca_system_score_codex":0.00020563738,"about_ca_system_score_gemma":0.000120577206,"threshold_uncertainty_score":0.99712956},"labels":[],"label_agreement":null}]}