{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":3,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":3,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"c12579eb3c5a","filters":{"venue":"DEMIS Demographic research"}},"results":[{"id":"W4361863893","doi":"10.19181/demis.2023.3.1.7","title":"Dynamics and Structure of International Labor Migration: Global Trends","year":2023,"lang":"en","type":"article","venue":"DEMIS Demographic research","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Workforce; Population; Scale (ratio); Human migration; Economics; Labour economics; Labor demand; Labor relations; Secondary labor market; Business; Economic growth; Geography; Wage","authors":[{"name":"Eteri Rubinskaya","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04659688227641231,"gpt":0.3986258510972032,"spread":0.3520289688207909,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005990672,0.0002502412,0.0002500013,0.003446409,0.0003585375,0.001187383,0.0002970939,0.0004601337,0.002854329],"category_scores_gemma":[0.00130039,0.0001147838,0.0003408444,0.00681671,0.0005633058,0.001445583,0.000763906,0.0005304319,0.0004946952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007785207,"about_ca_system_score_gemma":0.0007296042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005251045,"about_ca_topic_score_gemma":0.005631915,"domain_scores_codex":[0.9997423,0.00005131328,0.00003302835,0.00007418224,0.00004695171,0.00005225259],"domain_scores_gemma":[0.999238,0.0001296284,0.0002931659,0.00004421819,0.0002129959,0.00008196383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002519645,0.00007324017,0.7190323,0.001097044,0.0001469089,0.0002961177,0.009277229,0.00172671,0.002248117,0.02398588,0.006845717,0.2350188],"study_design_scores_gemma":[0.000004278428,0.0001121039,0.9459211,0.0002826833,0.00003703661,0.0006018483,0.005373139,0.0008998053,0.0002944488,0.001824049,0.04462857,0.00002086714],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9054647,0.04378852,0.002895949,0.005859649,0.0002865505,0.00007697986,0.005876583,0.0001559076,0.03559522],"genre_scores_gemma":[0.9766639,0.01616562,0.001436072,0.0002195273,0.0001746836,0.00003996745,0.00213658,0.00002607467,0.003137555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005251045,"threshold_uncertainty_score":0.01044095,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400118180","doi":"10.19181/demis.2024.4.2.8","title":"Functioning of the Chinese Diaspora in Canada: Demographic and Sociocultural Aspects","year":2024,"lang":"en","type":"article","venue":"DEMIS Demographic research","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Diaspora; Sociocultural evolution; Geography; Anthropology; Sociology; Gender studies","authors":[{"name":"Yi Fang Wang","is_ca":false},{"name":"Peng Lui","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03519360668128063,"gpt":0.328626415004546,"spread":0.2934328083232654,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008414953,0.0002415071,0.0002482725,0.002032851,0.01131586,0.003592965,0.0009581845,0.0003495104,0.002176635],"category_scores_gemma":[0.001407392,0.0001746477,0.000218954,0.003740367,0.003129888,0.0009317416,0.00242945,0.0006848084,0.0001690372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03760427,"about_ca_system_score_gemma":0.0586612,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9909546,"about_ca_topic_score_gemma":0.9951451,"domain_scores_codex":[0.9990112,0.0001443413,0.00002064998,0.00007376621,0.0001772508,0.0005728787],"domain_scores_gemma":[0.9986739,0.0001053022,0.0001304119,0.00003429126,0.000457939,0.0005981531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007258486,0.0001212731,0.7614741,0.00005638991,0.00002887953,0.0004450634,0.1957267,0.0001334096,0.0006751364,0.006846919,0.003224567,0.03119488],"study_design_scores_gemma":[0.000003436758,0.00002967907,0.6592438,0.00006273006,0.00001545177,0.000115419,0.3281211,0.0002623237,0.0001387029,0.0003370722,0.01163861,0.000031597],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905915,0.0004623254,0.00005386563,0.0009999791,0.000008251333,0.00002528795,0.0003709098,0.000004292415,0.007483557],"genre_scores_gemma":[0.997696,0.0005334264,0.00007781741,0.0001014376,0.000002846562,0.00001154729,0.0001485463,0.000002954091,0.001425476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03760427,"threshold_uncertainty_score":0.2728394,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7117450542","doi":"10.19181/demis.2025.5.4.7","title":"Clustering of Regions of the Far East by the Level of Health Determinants","year":2025,"lang":"","type":"article","venue":"DEMIS Demographic research","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Cluster analysis; Multivariate statistics; Fuzzy clustering; Silhouette; Fuzzy logic; Population; Relevance (law)","authors":[{"name":"E. V. Polyanskaya","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.339491252123711,"gpt":0.4890230175728997,"spread":0.1495317654491887,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008497208,0.0002907548,0.0004908866,0.003229378,0.0005967569,0.001449489,0.0003261813,0.0002787808,0.001633144],"category_scores_gemma":[0.001906664,0.000134704,0.0005279243,0.003011466,0.0005048455,0.0003154336,0.0008997645,0.0001764059,0.000326065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008515007,"about_ca_system_score_gemma":0.001186916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03070365,"about_ca_topic_score_gemma":0.03008092,"domain_scores_codex":[0.9994388,0.0001973512,0.00004217256,0.0001305074,0.00008673003,0.0001043771],"domain_scores_gemma":[0.9991087,0.0002369831,0.0002127141,0.0001266887,0.0002508424,0.00006405628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006357768,0.0001368706,0.8996336,0.0002914643,0.0005693407,0.0005531619,0.006191446,0.01878573,0.00673337,0.005719027,0.001453083,0.05929713],"study_design_scores_gemma":[0.00001242933,0.00007139276,0.9735917,0.00006178169,0.0001453368,0.0002287217,0.00733326,0.01221087,0.0009836087,0.002193881,0.003125495,0.00004158469],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916388,0.0005836567,0.004548469,0.00008578439,0.000009130765,0.00006376925,0.0005618604,0.00002662124,0.002481871],"genre_scores_gemma":[0.9954793,0.0001731089,0.003120052,0.00001361102,0.00000469865,0.00003164602,0.0005623393,0.000005985471,0.0006091725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03070365,"threshold_uncertainty_score":0.06104982,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}