{"meta":{"query_hash":"df94ee6c34f7","filters":{"venue":"Commodities"},"cohort_total":3,"direct_labels_cover":0,"predictions_cover":3,"exported":3,"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/df94ee6c34f7","api":"https://metacan.xera.ac/api/v1/cohort?venue=Commodities"},"results":[{"id":"W4380485414","doi":"10.3390/commodities2020011","title":"A Game-Theoretic Analysis of Canada’s Entry for LNG Exports in the Asia-Pacific Market","year":2023,"lang":"en","type":"article","venue":"Commodities","topic":"Global Energy Security and Policy","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Profitability index; Profit (economics); Stackelberg competition; Business; Competition (biology); Incentive; Industrial organization; Profit margin; Market share; International trade; Differential game; Economics; Microeconomics; Finance","score_opus":0.014780056538540054,"score_gpt":0.23733811774165128,"score_spread":0.22255806120311122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380485414","genre_codex":"other","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":[0.30462062,0.00026793862,0.0000075317203,0.0028079813,0.00027204552,0.00016146315,0.0004505557,0.000060357223,0.69135153],"genre_scores_gemma":[0.9958124,0.000057166857,0.000007755676,0.00026765832,0.000060957773,0.00006293647,0.00021666939,0.00001016585,0.0035042728],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989371,0.00014671593,0.00025406116,0.00013179779,0.000215059,0.00031527324],"domain_scores_gemma":[0.9989586,0.00052036013,0.000076100136,0.00037030975,0.000034560453,0.000040084964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036886797,0.00011713392,0.0002772924,0.0002490345,0.00007420641,0.000023339831,0.00030098503,0.00005945911,0.00022354512],"category_scores_gemma":[0.000101422724,0.00009456365,0.00013940468,0.0008674671,0.00010845815,0.000041030296,0.000041036685,0.00008035585,0.0000017803891],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028057537,0.000019704652,0.00034229056,0.000044416545,0.00016333738,0.000013921892,0.002498356,0.0061902143,0.0000033159909,0.89373887,0.0966155,0.00034198636],"study_design_scores_gemma":[0.0002808874,0.000029599578,0.016738886,0.000032882384,0.00021763526,0.000002918991,0.010926681,0.0049376744,0.00018270059,0.038228262,0.92823327,0.00018862452],"about_ca_topic_score_codex":0.33536443,"about_ca_topic_score_gemma":0.8693793,"teacher_disagreement_score":0.85551065,"about_ca_system_score_codex":0.00005911632,"about_ca_system_score_gemma":0.00017475484,"threshold_uncertainty_score":0.6690614},"labels":[],"label_agreement":null},{"id":"W4408052245","doi":"10.3390/commodities4010002","title":"Causality Between Brent and West Texas Intermediate: The Effects of COVID-19 Pandemic and Russia–Ukraine War","year":2025,"lang":"en","type":"article","venue":"Commodities","topic":"Global Energy and Sustainability Research","field":"Energy","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":"Concordia University","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Causality (physics); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Political science; History; Virology; Medicine; Outbreak; Physics","score_opus":0.02228378071381665,"score_gpt":0.3132812659306085,"score_spread":0.29099748521679186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408052245","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":[0.9907915,0.0034592953,0.00007208763,0.0018396226,0.00011306891,0.00020752267,0.000032771834,0.000051461197,0.003432641],"genre_scores_gemma":[0.99810284,0.0006253409,0.000004791755,0.00030395717,0.000050354483,0.000027178708,0.000023909213,0.000006479025,0.0008551442],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99872595,0.000418343,0.00022883424,0.00020584997,0.0001627194,0.00025831105],"domain_scores_gemma":[0.9972551,0.0021595457,0.00004606312,0.00035222823,0.000060557242,0.00012654215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005308303,0.00014352651,0.000294662,0.00007676047,0.0002062446,0.00003283454,0.00024571925,0.000107195134,0.000027233062],"category_scores_gemma":[0.0013471416,0.00009831945,0.0000437307,0.00015000865,0.0010649874,0.00006404543,0.00041987665,0.00023354637,0.0000015482418],"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":[0.00016962817,0.000091033944,0.72454965,0.0035760268,0.0002552848,0.000018220373,0.0032417905,0.000118795026,0.00006239777,0.23096742,0.002390947,0.03455882],"study_design_scores_gemma":[0.0016703058,0.00025819187,0.7500253,0.00014451535,0.00010151055,0.00000823435,0.0029335879,0.00017248721,0.0007041195,0.15696275,0.0867664,0.00025265088],"about_ca_topic_score_codex":0.005468377,"about_ca_topic_score_gemma":0.0014063847,"teacher_disagreement_score":0.08437545,"about_ca_system_score_codex":0.00011744466,"about_ca_system_score_gemma":0.00016141577,"threshold_uncertainty_score":0.82665867},"labels":[],"label_agreement":null},{"id":"W4408714029","doi":"10.3390/commodities4020004","title":"Wavelet Entropy for Efficiency Assessment of Price, Return, and Volatility of Brent and WTI During Extreme Events","year":2025,"lang":"en","type":"article","venue":"Commodities","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Volatility (finance); Economics; Econometrics","score_opus":0.02781370027193509,"score_gpt":0.253130225031257,"score_spread":0.2253165247593219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408714029","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":[0.98455834,0.0009794906,0.009991289,0.000105576146,0.00013249283,0.00028277343,0.00043077662,0.0000065687586,0.003512681],"genre_scores_gemma":[0.9985259,0.00016593133,0.0009208799,0.000008787711,0.000009080514,0.000016574368,0.000012132195,0.0000048429256,0.00033587325],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990929,0.000016833766,0.0005088992,0.00021677396,0.000030122976,0.00013448959],"domain_scores_gemma":[0.99927914,0.0001461876,0.00026288995,0.00023468587,0.00004876408,0.000028357177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004969309,0.000096682415,0.00036690928,0.00012287039,0.00007741012,0.000014796977,0.00010156294,0.000050224895,0.00003732856],"category_scores_gemma":[0.00009104104,0.00010552092,0.000057974357,0.00008021085,0.00009610452,0.000071961396,0.00011592868,0.000065406624,3.9311065e-8],"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":[0.000035633144,0.000101610356,0.9347837,0.0007714585,0.000038737584,7.256855e-8,0.00017138745,0.0000012436809,0.00007110134,0.063578665,0.000045396962,0.00040098323],"study_design_scores_gemma":[0.0005651503,0.000046083955,0.72532684,0.000045164383,0.000007125044,2.4266697e-7,0.000060528993,0.22807342,0.00009106563,0.045192994,0.0005122504,0.00007915063],"about_ca_topic_score_codex":0.00006271658,"about_ca_topic_score_gemma":0.00001835137,"teacher_disagreement_score":0.22807217,"about_ca_system_score_codex":0.000044548087,"about_ca_system_score_gemma":0.00002023641,"threshold_uncertainty_score":0.43030185},"labels":[],"label_agreement":null}]}