{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"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":"aa7522edc904","filters":{"venue":"Journal of Empirical Economics and Social Sciences"}},"results":[{"id":"W4313177120","doi":"10.46959/jeess.1087689","title":"THE RELATIONSHIP OF INFLATION, UNEMPLOYMENT AND ECONOMIC GROWTH PANEL DATA ANALYSIS IN SELECTED OECD COUNTRIES","year":2022,"lang":"en","type":"article","venue":"Journal of Empirical Economics and Social Sciences","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Cointegration; Economics; Unemployment; Unit root; Inflation (cosmology); Causality (physics); Econometrics; Context (archaeology); Unit root test; Panel data; Misery index; Macroeconomics; Unemployment rate; Geography","authors":[{"name":"Kerem ÖZEN","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09445865301104067,"gpt":0.2935066507737292,"spread":0.1990479977626886,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001408347,0.0002573264,0.0004795991,0.001996199,0.0002861698,0.001017501,0.0001526626,0.0002879078,0.001036072],"category_scores_gemma":[0.002823002,0.0001399802,0.0006753455,0.002922965,0.0001754332,0.0003573106,0.0005259261,0.0005047885,0.0002213649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006284862,"about_ca_system_score_gemma":0.0006464333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04125429,"about_ca_topic_score_gemma":0.04232212,"domain_scores_codex":[0.9993513,0.0002570309,0.00005875947,0.00007282459,0.0000976259,0.0001624841],"domain_scores_gemma":[0.9976597,0.0009709239,0.0007031193,0.0001765932,0.0003518308,0.0001378479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001170108,0.00005437261,0.9871823,0.00005026717,0.0003524977,0.000238905,0.0001518655,0.005209628,0.0001594425,0.0004084999,0.00157635,0.004498846],"study_design_scores_gemma":[0.000006390785,0.00003397739,0.9931163,0.00002882406,0.0001251233,0.00007676826,0.0006946036,0.003766418,0.0001939086,0.0001531275,0.001792033,0.00001249618],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922253,0.0006034259,0.0004993412,0.0001595004,0.00001475489,0.00001251608,0.004792777,0.00001734397,0.00167507],"genre_scores_gemma":[0.9891042,0.0005413352,0.0003616915,0.00005205347,0.00001602845,0.00003036147,0.009522523,0.000005520184,0.0003662951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04125429,"threshold_uncertainty_score":0.08202833,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404099359","doi":"10.46959/jeess.1556704","title":"ANALYSIS OF SELECTED COUNTRIES ACCORDING TO THEIR ENERGY CONSUMPTION BY CLUSTER ANALYSIS K-MEANS METHOD","year":2024,"lang":"en","type":"article","venue":"Journal of Empirical Economics and Social Sciences","topic":"Energy Load and Power Forecasting","field":"Engineering","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 (spacecraft); Consumption (sociology); Energy consumption; Statistics; Computer science; Mathematics; Engineering; Sociology; Social science; Electrical engineering","authors":[{"name":"Şakir İşleyen","is_ca":false},{"name":"Nazer Mhmadamın Mhmadshrif","is_ca":false},{"name":"Çetin Görür","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0294184262969086,"gpt":0.3132263216954483,"spread":0.2838078953985397,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001630254,0.001082267,0.00124346,0.007376013,0.001074047,0.001608351,0.0008384495,0.0005035573,0.003070412],"category_scores_gemma":[0.005012628,0.0003213814,0.001770849,0.009808576,0.0003950589,0.0005887639,0.0009925138,0.0005828728,0.00093934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009028066,"about_ca_system_score_gemma":0.001796755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0173029,"about_ca_topic_score_gemma":0.01216711,"domain_scores_codex":[0.9981971,0.0004590484,0.0002342013,0.0004714802,0.0004020785,0.0002361118],"domain_scores_gemma":[0.9981055,0.0005405673,0.0002344509,0.0002222547,0.0008279292,0.00006930256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001846667,0.0009077908,0.4016114,0.002571137,0.00304214,0.0009853742,0.007087202,0.1002689,0.0077227,0.009297086,0.02799447,0.4366651],"study_design_scores_gemma":[0.0002109855,0.000735681,0.5584635,0.000701225,0.001700439,0.0005663436,0.02297618,0.3199828,0.01234683,0.01263506,0.06929081,0.0003901331],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7889969,0.001248792,0.1745522,0.0003436373,0.0002758823,0.002919256,0.01640324,0.001307764,0.01395229],"genre_scores_gemma":[0.8423666,0.0008260035,0.1306774,0.00006340041,0.00006339829,0.002688208,0.01873652,0.0001817415,0.004396819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0173029,"threshold_uncertainty_score":0.0344044,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}