{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":13,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":13,"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"},"query_hash":"0b88ee2472c2","filters":{"venue":"Journal of commodity markets"}},"results":[{"id":"W2975391820","doi":"10.1016/j.jcomm.2019.100107","title":"Econometric modelling and forecasting of intraday electricity prices","year":2019,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Narodowym Centrum Nauki; Narodowe Centrum Nauki; Deutsche Forschungsgemeinschaft","keywords":"Econometrics; Lasso (programming language); Electricity price forecasting; Benchmark (surveying); Electricity market; Economics; Electricity; Sample (material); Multivariate statistics; Econometric model; Quarter (Canadian coin); Computer science; Statistics; Mathematics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01733338125675517,"gpt":0.1924414586771334,"spread":0.1751080774203782,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007848103,0.0001125471,0.0003439239,0.0003340722,0.00002786935,0.00002626351,0.0001488915,0.00006054267,0.00002937293],"category_scores_gemma":[0.0000670236,0.0001029252,0.00008015383,0.0002761266,0.0000155735,0.0002932075,0.00002751847,0.0002812592,7.705302e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003902152,"about_ca_system_score_gemma":0.00001941685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004889087,"about_ca_topic_score_gemma":0.000001959752,"domain_scores_codex":[0.9990549,0.00003127648,0.0005150868,0.00006624183,0.000156819,0.0001756713],"domain_scores_gemma":[0.9989914,0.0004635498,0.0002946721,0.0000942726,0.00008088384,0.00007525083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009045903,0.00004162032,0.01954348,0.0004213624,0.0001589433,0.000007562238,0.0002318585,0.939552,0.0007270138,0.0002925675,0.0002408488,0.03869228],"study_design_scores_gemma":[0.0005238285,0.0001262987,0.006061164,0.0001836639,0.00002660203,0.0001126881,0.00002375442,0.9865762,0.00365983,0.0005664162,0.001963191,0.000176383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783393,0.001579962,0.01009453,0.00001176496,0.0003428895,0.00004102346,0.000003140284,0.00001354026,0.009573894],"genre_scores_gemma":[0.9960896,0.0003524995,0.003417408,0.000006795027,0.000100636,2.615885e-7,7.068459e-7,0.00001528248,0.00001679258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04702417,"threshold_uncertainty_score":0.4197166,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2514560096","doi":"10.1016/j.jcomm.2016.07.004","title":"Natural gas storage valuation, optimization, market and credit risk management","year":2016,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":23,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Valuation (finance); Hedge; Volatility (finance); Markov process; Valuation of options; Mathematical optimization; Econometrics; Computer science; Partial differential equation; Risk management; Economics; Mathematics; Finance; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.0144391909055022,"gpt":0.2137109738438132,"spread":0.199271782938311,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003991022,0.0001571415,0.0003905599,0.0002617705,0.0001384813,0.00008809299,0.0002713769,0.00007479997,0.001395763],"category_scores_gemma":[0.000520387,0.0001280323,0.0001308429,0.0001392827,0.0000739074,0.0004718043,0.0001129667,0.000198408,0.00000636969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001420809,"about_ca_system_score_gemma":0.00001623043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007380414,"about_ca_topic_score_gemma":0.000008339116,"domain_scores_codex":[0.9984156,0.0001552976,0.0008795896,0.0002218189,0.0001212359,0.000206409],"domain_scores_gemma":[0.9979416,0.0002930028,0.001142023,0.0003114407,0.0001830578,0.0001288686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001511249,0.0005047038,0.7917373,0.0002075334,0.0009022846,0.00005570551,0.0002980161,0.0006484062,0.0000037793,0.02463587,0.08618016,0.09331504],"study_design_scores_gemma":[0.002051826,0.00008471575,0.5605446,0.0000692551,0.00004694119,0.00003551382,0.00002360193,0.3026226,0.000001266222,0.08884883,0.04539031,0.000280556],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4519636,0.004213973,0.4657635,0.003877258,0.002972574,0.0004784121,0.0003535229,0.00003544757,0.0703417],"genre_scores_gemma":[0.9863811,0.003746662,0.008253553,0.00007942453,0.0001841626,0.000003251647,0.000003864896,0.00001747753,0.00133052],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5344175,"threshold_uncertainty_score":0.9995171,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2921334691","doi":"10.1016/j.jcomm.2019.02.003","title":"Are crude oil markets cointegrated? Testing the co-movement of weekly crude oil spot prices","year":2019,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Crude oil; Spot contract; Cointegration; Economics; Econometrics; Environmental science; Petroleum engineering; Financial economics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03778781492514279,"gpt":0.2421234555280971,"spread":0.2043356406029543,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00623472,0.0003159204,0.001042572,0.0002919933,0.0001657234,0.0001512283,0.0009831704,0.0001636686,0.001292289],"category_scores_gemma":[0.001355431,0.0002560667,0.0003926984,0.0003897176,0.0001334714,0.0003668169,0.0001756607,0.0007512658,0.00003583748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002268812,"about_ca_system_score_gemma":0.0001019903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001288763,"about_ca_topic_score_gemma":0.00006784192,"domain_scores_codex":[0.9968669,0.0002014919,0.001906055,0.0003291886,0.0002653278,0.0004310707],"domain_scores_gemma":[0.9929496,0.001255476,0.004483316,0.0007289518,0.0004155092,0.0001671541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007736987,0.000619129,0.9677224,0.0005119379,0.000343215,0.00002891969,0.0001854544,0.00004785607,0.0003380076,0.001970123,0.01072326,0.01673598],"study_design_scores_gemma":[0.00139424,0.0001777427,0.9195961,0.0003980881,0.00003489874,0.00003835037,0.0002295209,0.01953234,0.0001551439,0.006469152,0.05160665,0.0003677332],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8863106,0.001104818,0.0001776377,0.001437918,0.0008273375,0.00009682833,0.000265595,0.00001319765,0.1097661],"genre_scores_gemma":[0.9957765,0.0004896389,0.0007459795,0.0004285125,0.0001688972,0.000004441038,0.000006941729,0.00003336424,0.002345711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1094659,"threshold_uncertainty_score":0.9999892,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3195693623","doi":"10.1016/j.jcomm.2023.100361","title":"Exploring volatility of crude oil intraday return curves: A functional GARCH-X model","year":2023,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Actua; University of Waterloo","funders":"","keywords":"Volatility (finance); Econometrics; Heteroscedasticity; Futures contract; Crude oil; Economics; Autoregressive conditional heteroskedasticity; Forward volatility; Realized variance; Financial economics; Volatility smile","retraction":null,"screen_n_in":null,"score":{"opus":0.1747106905939309,"gpt":0.2553569170207295,"spread":0.08064622642679867,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005392865,0.0001825998,0.0007261201,0.0004052398,0.00009869065,0.000033477,0.0003993706,0.00008955465,0.0004135255],"category_scores_gemma":[0.001006645,0.0001938487,0.0003722956,0.0004665764,0.00009678826,0.0006361217,0.0001486146,0.000528614,0.000009403144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001419618,"about_ca_system_score_gemma":0.0001014682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003135422,"about_ca_topic_score_gemma":0.00002412186,"domain_scores_codex":[0.9976242,0.000104384,0.001521092,0.0002416452,0.0002057345,0.0003029877],"domain_scores_gemma":[0.9975841,0.0004157501,0.001152089,0.0004420396,0.0002400405,0.0001660055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002831729,0.00141215,0.8559929,0.003520462,0.0009321197,0.0000603411,0.00148501,0.001978501,0.0003383736,0.0190373,0.086207,0.02620416],"study_design_scores_gemma":[0.0006729353,0.00006844966,0.289081,0.0002365009,0.00001767631,0.00001389881,0.00003433104,0.6647346,0.00002828423,0.03874386,0.006156807,0.0002116322],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795842,0.0008879213,0.006111063,0.00133816,0.0008299615,0.00006883038,0.0003019443,0.0000256172,0.01085236],"genre_scores_gemma":[0.9955403,0.003036546,0.0005681586,0.000095761,0.0001457158,0.00000696308,0.00001890097,0.00002086554,0.0005667892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6627561,"threshold_uncertainty_score":0.7904919,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2552095547","doi":"10.1016/j.jcomm.2016.11.003","title":"New indices of adequate and excess speculation and their relationship with volatility in the crude oil futures market","year":2016,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Speculation; Futures contract; Economics; Volatility (finance); Financial economics; Futures market; Hedge; Realized variance; Index (typography); Crude oil; Cash; Monetary economics; Finance; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.02296552896884486,"gpt":0.217837476593142,"spread":0.1948719476242972,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003433368,0.0001224196,0.0003580898,0.0001835104,0.00007213124,0.00005231471,0.0001971508,0.00007990362,0.0001728388],"category_scores_gemma":[0.0003141572,0.00006960015,0.00005500191,0.0001532815,0.00009616958,0.0003945951,0.00004268273,0.0002041171,2.360305e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003534857,"about_ca_system_score_gemma":0.00003267064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000094961,"about_ca_topic_score_gemma":0.0003572043,"domain_scores_codex":[0.9987797,0.0001849235,0.0006819316,0.0001503389,0.00007473597,0.0001283465],"domain_scores_gemma":[0.99774,0.001014451,0.0008918849,0.0002302059,0.00005368217,0.00006973204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004321021,0.00004454535,0.9750896,0.00004277089,0.00003201401,0.000001884658,0.0007075316,7.222534e-7,0.000003029072,0.004136174,0.0003270491,0.01918258],"study_design_scores_gemma":[0.0008156407,0.00007086136,0.9466084,0.00008234118,0.000007399991,0.00001932775,0.0001211252,0.002398946,0.000003080286,0.04856841,0.001217729,0.00008676112],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872863,0.001319616,0.003590583,0.00161428,0.00008670997,0.00007073559,0.00005392214,0.000002322234,0.005975511],"genre_scores_gemma":[0.9990206,0.0003016626,0.0004115553,0.00003094471,0.00006407647,0.000001269933,0.000001071156,0.000006652313,0.0001621378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04443223,"threshold_uncertainty_score":0.2838212,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4212851779","doi":"10.1016/j.jcomm.2022.100247","title":"Interfuel substitution: A copula approach","year":2022,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lakehead University; University of Calgary","funders":"","keywords":"Substitution (logic); Copula (linguistics); Normality; Econometrics; Computer science; Coal; Economics; Mathematics; Statistics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.03367496191483896,"gpt":0.2262354664534819,"spread":0.192560504538643,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003429054,0.0001170223,0.0004384934,0.0002354599,0.0002365598,0.00005771715,0.0005079561,0.00004387939,0.001831874],"category_scores_gemma":[0.000163098,0.0001314184,0.000246677,0.0002293892,0.00005544933,0.0002097951,0.0002209418,0.0005665427,0.000007282337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002624455,"about_ca_system_score_gemma":0.00004721598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002001461,"about_ca_topic_score_gemma":0.000003010196,"domain_scores_codex":[0.9985314,0.0001268672,0.0008710448,0.0001698514,0.0001110568,0.0001897805],"domain_scores_gemma":[0.9985787,0.00008691111,0.0008661891,0.0003008445,0.00006460146,0.000102707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001551808,0.002214962,0.6880237,0.0001865219,0.0003948948,0.00009447425,0.000735603,0.0007057374,0.00001290556,0.2448428,0.05698027,0.004256404],"study_design_scores_gemma":[0.001825,0.0002858447,0.1717826,0.00001470289,0.00002095348,0.0004652719,0.0001554438,0.1574287,0.000003251042,0.0886226,0.5789884,0.0004073067],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8414986,0.0019906,0.02313885,0.0009168464,0.001951483,0.0001777517,0.0002835028,0.00001719091,0.1300252],"genre_scores_gemma":[0.9980844,0.00005549672,0.001039847,0.0001699274,0.0001282888,0.000006691469,0.00001291713,0.00001139707,0.0004910569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5220081,"threshold_uncertainty_score":0.9990806,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404360577","doi":"10.1016/j.jcomm.2024.100447","title":"Carbon pricing and the commodity risk premium","year":2024,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"","keywords":"Commodity; Economics; Risk premium; Business; Price risk; Financial economics; Commerce; Futures contract; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.0146969835714228,"gpt":0.2181068007919489,"spread":0.2034098172205261,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007513071,0.0001508953,0.0005262982,0.0001637169,0.0001454401,0.0002307259,0.0003134813,0.00009252305,0.00009255661],"category_scores_gemma":[0.0006129972,0.0001118013,0.000219351,0.0001795994,0.0001727133,0.0002126869,0.0001373379,0.0007573764,0.000003165921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001014999,"about_ca_system_score_gemma":0.00003678474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001901984,"about_ca_topic_score_gemma":0.00004747269,"domain_scores_codex":[0.998447,0.0002182711,0.0008541703,0.0001929782,0.00008759773,0.0002000046],"domain_scores_gemma":[0.9978884,0.001026293,0.0006004997,0.0003250925,0.00006260209,0.00009713414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001626912,0.0002630196,0.826502,0.0005679844,0.0009073254,0.00006871056,0.00215937,0.00006048471,0.000006979446,0.1282846,0.01370395,0.02584864],"study_design_scores_gemma":[0.001303367,0.00006482734,0.2015234,0.0001053134,0.00006239022,0.00008819601,0.00003324325,0.5380766,0.000004656076,0.1952576,0.06326978,0.0002106458],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9447041,0.00993301,0.002516763,0.002489255,0.001377766,0.0001813954,0.0001266695,0.00002019907,0.03865082],"genre_scores_gemma":[0.9976491,0.001609044,0.0001927292,0.00007966909,0.0002580064,0.000002407818,0.000001697908,0.0000156811,0.0001916844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6249787,"threshold_uncertainty_score":0.4559123,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403263861","doi":"10.1016/j.jcomm.2024.100439","title":"Expected returns on commodity ETFs and their underlying assets","year":2024,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Commodity; Business; Financial economics; Economics; Monetary economics; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.05705047268595134,"gpt":0.2686745841017297,"spread":0.2116241114157783,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002806298,0.0002270071,0.0006051291,0.0003471201,0.0001456342,0.0003036279,0.000306586,0.0001552833,0.0003344699],"category_scores_gemma":[0.0003239461,0.0002009753,0.0002428809,0.0002236754,0.00007925421,0.0003712755,0.0001017674,0.0007775908,0.00001194518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000178261,"about_ca_system_score_gemma":0.00004729108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002323806,"about_ca_topic_score_gemma":0.00004215271,"domain_scores_codex":[0.998349,0.0001368483,0.0008824853,0.000281967,0.00008766255,0.0002620388],"domain_scores_gemma":[0.9981642,0.0007760527,0.0004544235,0.0003553403,0.00007476855,0.0001752185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002252059,0.00191097,0.5115175,0.001564704,0.002287515,0.0005035106,0.005463693,0.0000654965,0.0003199386,0.2641624,0.1212624,0.08868986],"study_design_scores_gemma":[0.001071527,0.00040912,0.4839443,0.0004047885,0.00002677243,0.0001956445,0.0001661559,0.1392158,0.00003610854,0.2484266,0.1255182,0.0005849016],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675153,0.003298146,0.003590432,0.002341957,0.001355421,0.0001314768,0.0003020797,0.00003945936,0.02142573],"genre_scores_gemma":[0.9987422,0.0004862642,0.0002325396,0.0001576457,0.0001700761,0.00000217962,0.00001022958,0.00002580353,0.0001731132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1391503,"threshold_uncertainty_score":0.8195534,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4306315035","doi":"10.1016/j.jcomm.2022.100292","title":"Equilibrium and real options in the ethanol industry: Modeling and empirical evidence","year":2022,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mandate; Gasoline; Economics; Valuation (finance); Government (linguistics); Ethanol; Ethanol fuel; Agricultural economics; Chemistry; Finance; Engineering; Waste management","retraction":null,"screen_n_in":null,"score":{"opus":0.143515098508165,"gpt":0.3039741513291695,"spread":0.1604590528210045,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002403841,0.00007067865,0.0002475887,0.0002295843,0.0001027445,0.0000791121,0.0002055844,0.00005734759,0.0001141186],"category_scores_gemma":[0.0001121711,0.00005981873,0.00007406143,0.0001996197,0.00004846777,0.0002888399,0.0001584849,0.0006480752,0.000001342032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006323604,"about_ca_system_score_gemma":0.00002483475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001213281,"about_ca_topic_score_gemma":0.00002212881,"domain_scores_codex":[0.9990873,0.0001409955,0.0004588983,0.000114649,0.00007988619,0.0001182604],"domain_scores_gemma":[0.9993137,0.0002198437,0.000260897,0.0001308313,0.00001937846,0.00005538858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005076146,0.0007301235,0.8632687,0.00006780057,0.0002757005,0.0001558102,0.00923678,0.01260978,0.00009171568,0.09473088,0.01685597,0.001469152],"study_design_scores_gemma":[0.001164009,0.0004028635,0.3622454,0.00006056863,0.00007711094,0.0003431133,0.002211348,0.4693729,0.000004420852,0.1576104,0.006151515,0.0003562877],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754258,0.01620632,0.00003606962,0.00751062,0.00009222436,0.00005522247,0.00001750029,0.000002295198,0.0006539115],"genre_scores_gemma":[0.9931785,0.006271743,0.0001031435,0.0003071862,0.00006721234,0.000004071552,0.000001221105,0.000004771017,0.00006213481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5010232,"threshold_uncertainty_score":0.28156,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410029518","doi":"10.1016/j.jcomm.2025.100476","title":"Extremal dependence in Australian electricity markets","year":2025,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Electricity; Economics; Business; Telecommunications; Physics; Computer science; Quantum mechanics","retraction":null,"screen_n_in":null,"score":{"opus":0.02414904152896247,"gpt":0.2518468589372821,"spread":0.2276978174083197,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004425124,0.0001886722,0.0006647735,0.0006816103,0.00007838901,0.00009158385,0.0005991666,0.0001753944,0.0006499167],"category_scores_gemma":[0.0008022105,0.0002089122,0.000236358,0.0006130812,0.00005671594,0.0003659218,0.0001065408,0.0006943074,0.000009708672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003117911,"about_ca_system_score_gemma":0.0001073868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001031056,"about_ca_topic_score_gemma":0.000232244,"domain_scores_codex":[0.9977436,0.0001548927,0.001362431,0.0002635262,0.0001001936,0.0003753331],"domain_scores_gemma":[0.9983021,0.0003485241,0.0007557333,0.0003683527,0.0001089312,0.0001163338],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005741373,0.000351451,0.9715008,0.00008023423,0.00007334024,0.00005729482,0.00004221711,0.00001324489,0.00001887892,0.01265204,0.007890367,0.006746045],"study_design_scores_gemma":[0.0009282777,0.00004388038,0.8774959,0.00008092331,0.000008457324,0.00002310996,0.00001278059,0.01700176,0.00002778024,0.06839371,0.03579795,0.0001854181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9171576,0.0009215963,0.003724001,0.002091934,0.0008175358,0.0001663499,0.00004845466,0.00001081273,0.0750617],"genre_scores_gemma":[0.9969151,0.0002752552,0.0006358446,0.0001779168,0.00006265986,0.000002858645,0.000002352904,0.000009894952,0.001918102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09400479,"threshold_uncertainty_score":0.8519192,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2779128009","doi":"10.1016/j.jcomm.2017.12.006","title":"Country of origin growth modelling for imported salted &amp; dried (Klippfisk) products to Brazil","year":2017,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Norges Teknisk-Naturvitenskapelige Universitet","keywords":"Dried fish; Salted fish; Fish <Actinopterygii>; Fishery; Fish products; Product (mathematics); Portuguese; Pollock; Quality (philosophy); Food science; Business; Biology; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.05875341318764992,"gpt":0.2702996996919415,"spread":0.2115462865042916,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026482,0.0002406924,0.00097826,0.0004216947,0.0002866539,0.0001948151,0.0009997692,0.0001703997,0.00005565145],"category_scores_gemma":[0.00111669,0.0002414132,0.0002774849,0.000165371,0.00007795694,0.0007482287,0.0001311763,0.0003021162,0.0000188198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009680427,"about_ca_system_score_gemma":0.0000881257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007827633,"about_ca_topic_score_gemma":0.00007298183,"domain_scores_codex":[0.9976802,0.00002783613,0.001512398,0.0003265857,0.00009348094,0.0003595114],"domain_scores_gemma":[0.9952687,0.0002016197,0.00301536,0.0007119899,0.0005818962,0.000220422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006837141,0.001931512,0.1666075,0.001197,0.002093744,0.00002727959,0.001114685,0.002150593,0.0018925,0.1018489,0.7120897,0.002209488],"study_design_scores_gemma":[0.006306942,0.0008137787,0.2370792,0.000333452,0.0001588436,0.00009498371,0.00005441009,0.003785984,0.001945876,0.1082081,0.6399209,0.001297531],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9676316,0.0007610462,0.009164386,0.004143615,0.001689951,0.0005529098,0.0004792518,0.00001600652,0.01556122],"genre_scores_gemma":[0.9881679,0.0006753299,0.009787716,0.000247933,0.0006343346,0.000009682582,0.00002764088,0.00003368485,0.0004158171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07216879,"threshold_uncertainty_score":0.9844546,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401798623","doi":"10.1016/j.jcomm.2024.100425","title":"Diversifying crude oil price risk with crude oil volatility index: The role of volatility-of-volatility","year":2024,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Accounting and Finance Association of Australia and New Zealand","keywords":"Volatility (finance); Crude oil; Economics; Volatility swap; Volatility risk premium; Volatility smile; Monetary economics; Financial economics; Implied volatility; Engineering; Petroleum engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.0129802677207397,"gpt":0.2127169826028744,"spread":0.1997367148821347,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008455656,0.0003893868,0.001221185,0.0003824756,0.000279794,0.0001491033,0.001014363,0.0002523956,0.0007000241],"category_scores_gemma":[0.00113462,0.0003074401,0.0006150746,0.0007349939,0.0004006539,0.000770837,0.0003281937,0.001386329,0.000004183524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002948007,"about_ca_system_score_gemma":0.0002369181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000711581,"about_ca_topic_score_gemma":0.0002743587,"domain_scores_codex":[0.9959729,0.0004415215,0.002234581,0.0005033679,0.0003894285,0.0004582331],"domain_scores_gemma":[0.9942945,0.001630368,0.002340219,0.001048748,0.0004683294,0.0002178911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001133145,0.0003744105,0.9687665,0.0005967476,0.0004936626,0.000008679719,0.0008864625,0.0000283078,0.00002705476,0.001487958,0.0003161487,0.02588089],"study_design_scores_gemma":[0.0006609288,0.0001533963,0.5818128,0.0002277445,0.00009370081,0.00001780602,0.0001610493,0.3769571,0.00005488972,0.01988708,0.01971115,0.0002623771],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9652994,0.005850066,0.003800004,0.0003492988,0.0005831283,0.0001223173,0.0007837212,0.00002630384,0.0231858],"genre_scores_gemma":[0.9980732,0.0007323251,0.0006919472,0.00002954614,0.0001410914,0.000004583071,0.000008213007,0.00003378807,0.0002853103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3869537,"threshold_uncertainty_score":0.9999378,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399913122","doi":"10.1016/j.jcomm.2024.100419","title":"Nash equilibria in greenhouse gas offset credit markets","year":2024,"lang":"en","type":"article","venue":"Journal of commodity markets","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Greenhouse gas; Offset (computer science); Carbon offset; Monte Carlo method; Economics; Nash equilibrium; Homogeneous; Optimal control; Mathematical optimization; Microeconomics; Computer science; Econometrics; Mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.06532144771304554,"gpt":0.2672956978993558,"spread":0.2019742501863103,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002781896,0.0002136455,0.0006801221,0.0007788041,0.00005381499,0.0002386863,0.0004770206,0.0001720234,0.001632988],"category_scores_gemma":[0.000305515,0.0002386526,0.0003119248,0.0002991035,0.0000669319,0.0007720162,0.0001551093,0.0005647271,0.0004001369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003258163,"about_ca_system_score_gemma":0.00005989753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007137793,"about_ca_topic_score_gemma":0.0001533516,"domain_scores_codex":[0.997806,0.00006391283,0.001379473,0.0002657163,0.00006755064,0.0004173617],"domain_scores_gemma":[0.9985446,0.0003962228,0.0005127991,0.0003303731,0.00003771132,0.0001783325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001988216,0.001227266,0.1379745,0.001233797,0.0007283834,0.001246536,0.003540651,0.0001254482,0.0001528714,0.08348792,0.7380432,0.03025121],"study_design_scores_gemma":[0.001991298,0.0002457094,0.1140025,0.000496143,0.00003007041,0.0004906344,0.0001308252,0.03638924,0.00006515443,0.1472965,0.6981559,0.0007059949],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9577852,0.004891967,0.0001401445,0.004903712,0.002747725,0.0001169074,0.0004434978,0.000032427,0.0289384],"genre_scores_gemma":[0.9946789,0.00318149,0.0002220607,0.000325159,0.00101165,0.000004543266,0.00001505639,0.00004624519,0.0005149257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06380857,"threshold_uncertainty_score":0.9992797,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}