{"meta":{"query_hash":"fe367e0614b3","filters":{"venue":"China Agricultural Economic Review"},"cohort_total":9,"direct_labels_cover":0,"predictions_cover":9,"exported":9,"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/fe367e0614b3","api":"https://metacan.xera.ac/api/v1/cohort?venue=China+Agricultural+Economic+Review"},"results":[{"id":"W1992617601","doi":"10.1108/17561371011044270","title":"A decision framework for optimal crop reinsurance selection","year":2010,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Reinsurance; Crop insurance; Business; Profitability index; Actuarial science; Adverse selection; Finance; Agriculture","score_opus":0.009475930800261266,"score_gpt":0.2512244850929,"score_spread":0.24174855429263875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992617601","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022545364,0.0017839129,0.9414715,0.002966384,0.00018079618,0.0003490762,0.0005585323,0.00013810018,0.03000638],"genre_scores_gemma":[0.7912111,0.0037861483,0.18309438,0.0005951371,0.00029873292,0.0007529601,0.0005466608,0.00007969505,0.019635186],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964837,0.0019203766,0.00012394768,0.0006044292,0.00041991466,0.00044763353],"domain_scores_gemma":[0.9952426,0.0034455706,0.00042591654,0.000090044974,0.0004980841,0.00029779767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00694344,0.0017510526,0.0024927657,0.00148434,0.0009092136,0.0039552194,0.0021470534,0.0032101457,0.011682605],"category_scores_gemma":[0.008934982,0.0009373606,0.0016928093,0.0012767372,0.0022923716,0.0029257373,0.0019504162,0.0034998516,0.0008934499],"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":[0.00009586035,0.0001338331,0.00071225857,0.00021332999,0.000074395844,0.00025353598,0.00017874416,0.6957947,0.0006774294,0.28571248,0.0033322705,0.012821165],"study_design_scores_gemma":[0.000059493344,0.00011810369,0.0003971327,0.00007157881,0.00005362258,0.000059698803,0.000110159934,0.9071472,0.00018954951,0.08815442,0.0035964004,0.000042643172],"about_ca_topic_score_codex":0.011301913,"about_ca_topic_score_gemma":0.0067614457,"teacher_disagreement_score":0.011682605,"about_ca_system_score_codex":0.004786162,"about_ca_system_score_gemma":0.004421866,"threshold_uncertainty_score":0.03908217},"labels":[],"label_agreement":null},{"id":"W2008437504","doi":"10.1108/17561371111192301","title":"Factors affecting crop insurance purchases in China: the Inner Mongolia region","year":2011,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Crop insurance; Agriculture; Business; China; Government (linguistics); Agricultural economics; Crop; Probit model; Probit; Agricultural science; Economics; Geography; Econometrics","score_opus":0.03791372679648035,"score_gpt":0.2265652724161261,"score_spread":0.18865154561964576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008437504","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99941385,0.00013257503,0.000037607548,0.00010543476,0.0000015120802,0.0000040502855,0.00006375553,0.0000013453235,0.00023983652],"genre_scores_gemma":[0.99957985,0.00008452296,0.000047499572,0.000018368371,0.0000014388894,0.000003921552,0.00007127586,5.1166995e-7,0.0001925302],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997062,0.00008346533,0.00002093556,0.00004638905,0.000040442614,0.00010252235],"domain_scores_gemma":[0.9988931,0.00023182755,0.00047711807,0.00005802502,0.00011328399,0.00022673128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066629547,0.00022033857,0.00016528374,0.0005372103,0.0007473112,0.0005134827,0.000400399,0.0002544323,0.0012537714],"category_scores_gemma":[0.0009248873,0.00013888236,0.00028156603,0.000890993,0.00040553958,0.00040595868,0.00048585187,0.00020727092,0.000094398056],"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":[0.000011483237,0.0000197978,0.99433714,0.0000275286,0.00002508203,0.00014541714,0.0021077322,0.0002508568,0.00020917914,0.000112036454,0.00014889629,0.0026048117],"study_design_scores_gemma":[0.0000013616811,0.000019481786,0.9947455,0.000018657372,0.000011616531,0.00005622541,0.004060076,0.0005574853,0.000046623485,0.00003153349,0.00044744014,0.000004009282],"about_ca_topic_score_codex":0.16363807,"about_ca_topic_score_gemma":0.16209699,"teacher_disagreement_score":0.16363807,"about_ca_system_score_codex":0.001597472,"about_ca_system_score_gemma":0.0019298916,"threshold_uncertainty_score":0.32537115},"labels":[],"label_agreement":null},{"id":"W2605941653","doi":"10.1108/caer-08-2015-0105","title":"A bootstrap approach for pricing crop yield insurance","year":2017,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","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":"University of Manitoba","funders":"","keywords":"Econometrics; Crop insurance; Estimator; Monte Carlo method; Underwriting; Robustness (evolution); Profitability index; Credibility; Parametric statistics; Economics; Confidence interval; Point estimation; Actuarial science; Statistics; Computer science; Mathematics; Agriculture; Finance","score_opus":0.044813928673475896,"score_gpt":0.2646409103776298,"score_spread":0.21982698170415393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605941653","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022417653,0.00140709,0.9703387,0.00042265307,0.00010201366,0.00010208958,0.000099172226,0.0002498419,0.0048607723],"genre_scores_gemma":[0.7297503,0.002052491,0.26438197,0.00020104248,0.00034690346,0.00029040233,0.00024963272,0.000112367736,0.0026147978],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973591,0.0015419646,0.000094486226,0.00023826666,0.0006606902,0.00010537756],"domain_scores_gemma":[0.99210256,0.005823482,0.00047950714,0.00049209374,0.0009709441,0.00013149138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005041055,0.0007091252,0.00096019875,0.0018760916,0.000404516,0.0010070192,0.0017602443,0.0012398455,0.0034610773],"category_scores_gemma":[0.021875573,0.00035911574,0.00093921827,0.0016624058,0.0007874986,0.0017484049,0.0010054887,0.0017162045,0.0004466512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030028753,0.00017014556,0.0063453033,0.0005269167,0.00020497837,0.00075991225,0.00037217044,0.50293237,0.0039452403,0.2270843,0.004670588,0.2526878],"study_design_scores_gemma":[0.000018011637,0.00007510705,0.0010859771,0.00004541055,0.000025740215,0.0001407484,0.0000517064,0.9565112,0.0005966464,0.039494637,0.0019285263,0.00002630714],"about_ca_topic_score_codex":0.0028470452,"about_ca_topic_score_gemma":0.0017227599,"teacher_disagreement_score":0.005041055,"about_ca_system_score_codex":0.00088266475,"about_ca_system_score_gemma":0.00077469565,"threshold_uncertainty_score":0.026659906},"labels":[],"label_agreement":null},{"id":"W2737160284","doi":"10.1108/caer-10-2016-0177","title":"The value of a novel biotechnology","year":2017,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"Innovation Policy and R&D","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":true,"ca_institutions":"University of Lethbridge; University of Manitoba","funders":"","keywords":"Incentive; Agricultural biotechnology; Canola; China; Private sector; Agriculture; Intellectual property; Investment (military); Productivity; Business; Work (physics); Public sector; Economics; Value (mathematics); Biotechnology; Agricultural economics; Public economics; Economic growth; Political science; Economy; Engineering; Market economy; Biology","score_opus":0.03860529948563912,"score_gpt":0.2634276802061677,"score_spread":0.22482238072052857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2737160284","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037033603,0.04093505,0.015839625,0.14589994,0.003606527,0.00013953324,0.0003642246,0.0003051327,0.7558763],"genre_scores_gemma":[0.7551418,0.059038028,0.020057576,0.0389139,0.0023406541,0.0001291807,0.00026979242,0.00013882903,0.123970255],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974228,0.0005743064,0.000057800924,0.0003946339,0.001188591,0.00036188852],"domain_scores_gemma":[0.99610597,0.001154713,0.0003272837,0.0009183127,0.0010302608,0.00046354267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032987595,0.00046370554,0.0004018655,0.00087799097,0.002486746,0.007465924,0.0012682067,0.0025171044,0.0137917055],"category_scores_gemma":[0.0045179497,0.00015182066,0.0005931901,0.00090767245,0.012440615,0.005026684,0.002465153,0.0024062789,0.0023891781],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009150272,0.00007531886,0.0024743392,0.00066824234,0.000062137195,0.00070050906,0.0011653575,0.0011112806,0.004667291,0.85331994,0.023727657,0.111936405],"study_design_scores_gemma":[0.000021961527,0.00011666889,0.0022459282,0.00075489085,0.000059083315,0.00063588616,0.0017151866,0.0008850517,0.0037139033,0.17875579,0.81105274,0.000042958003],"about_ca_topic_score_codex":0.034459237,"about_ca_topic_score_gemma":0.033583466,"teacher_disagreement_score":0.034459237,"about_ca_system_score_codex":0.011434304,"about_ca_system_score_gemma":0.016796054,"threshold_uncertainty_score":0.082962036},"labels":[],"label_agreement":null},{"id":"W2738000304","doi":"10.1108/caer-02-2017-0028","title":"Promise, problems and prospects: agri-biotech governance in China, India and Japan","year":2017,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Global Affairs Canada","funders":"","keywords":"Corporate governance; Incentive; Scarcity; China; Business; Agriculture; Biotechnology; Agricultural biotechnology; Population; International trade; Economic growth; Economics; Political science; Market economy; Finance; Biology","score_opus":0.005167503196766125,"score_gpt":0.24327993511836513,"score_spread":0.238112431921599,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2738000304","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91977346,0.002957062,0.0012960959,0.027326915,0.00007062261,0.00009132032,0.00007788087,0.00004134009,0.04836536],"genre_scores_gemma":[0.99532264,0.000712247,0.00030631784,0.0012294502,0.000013406491,0.000025104855,0.000029635921,0.0000037586688,0.002357434],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9981616,0.00053433515,0.000076424476,0.00018710476,0.00025017405,0.00079049077],"domain_scores_gemma":[0.99518627,0.00094621826,0.0012970435,0.00029335014,0.00059308246,0.0016840717],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0033200667,0.00017882716,0.00021192092,0.0009896372,0.0030499988,0.0070463354,0.0006340901,0.0013136762,0.0019100286],"category_scores_gemma":[0.0024559654,0.00019317467,0.0003042415,0.002227246,0.0069317124,0.0021901983,0.0038873318,0.0011896119,0.00009513736],"study_design_candidate":"qualitative","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":[0.0002997879,0.00040478446,0.43333688,0.00074232573,0.00014427035,0.0043685758,0.08349933,0.0035067494,0.0038487231,0.37708384,0.011148264,0.0816165],"study_design_scores_gemma":[0.00010320153,0.0003734402,0.659732,0.0006997311,0.00018389472,0.0005984698,0.19107139,0.0061765895,0.0018344988,0.043177202,0.09586599,0.00018358],"about_ca_topic_score_codex":0.09180184,"about_ca_topic_score_gemma":0.10271924,"teacher_disagreement_score":0.99695003,"about_ca_system_score_codex":0.010715936,"about_ca_system_score_gemma":0.017116688,"threshold_uncertainty_score":0.18253493},"labels":[],"label_agreement":null},{"id":"W2887649354","doi":"10.1108/caer-05-2017-0086","title":"Village-level supply reliability of groundwater irrigation in rural China","year":2018,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"Water resources management and optimization","field":"Engineering","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":"International Development Research Centre","funders":"","keywords":"Groundwater; Irrigation; Environmental science; Reliability (semiconductor); Precipitation; Water resource management; Hydrology (agriculture); Geography; Engineering; Meteorology; Ecology","score_opus":0.008334189203470368,"score_gpt":0.1960876567372759,"score_spread":0.18775346753380553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887649354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99937135,0.000018866338,0.00021090994,0.000024026413,5.71537e-7,0.0000023145153,0.00013018305,0.0000048366883,0.00023695653],"genre_scores_gemma":[0.9998636,0.0000061133155,0.00003074744,0.0000014588175,4.898072e-7,0.0000011454332,0.000051366173,4.9010526e-7,0.00004452491],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99902594,0.0003365088,0.000076427794,0.00020657777,0.00020185763,0.0001526558],"domain_scores_gemma":[0.9949008,0.0011584733,0.0021211677,0.0003926444,0.001076197,0.00035066003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010062093,0.00014218326,0.00024832622,0.0007426537,0.00030427167,0.00041846745,0.0003147838,0.00014779772,0.0009851031],"category_scores_gemma":[0.0043832003,0.00016607773,0.00027490643,0.0015489219,0.00046931594,0.00030470363,0.00054778834,0.00017020527,0.00009330684],"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":[0.00002132815,0.000009331042,0.99517846,0.000014274703,0.000032901447,0.00007697376,0.00043081646,0.0018835594,0.00035844068,0.00008910483,0.00007548466,0.0018294033],"study_design_scores_gemma":[0.0000019890651,0.000029313625,0.9958573,0.000003416369,0.000008817182,0.000031882424,0.00048025794,0.0032855547,0.00008378883,0.00009592009,0.000116286676,0.000005466563],"about_ca_topic_score_codex":0.041406836,"about_ca_topic_score_gemma":0.04363558,"teacher_disagreement_score":0.041406836,"about_ca_system_score_codex":0.0008187379,"about_ca_system_score_gemma":0.0007020934,"threshold_uncertainty_score":0.08233166},"labels":[],"label_agreement":null},{"id":"W4313430432","doi":"10.1108/caer-07-2022-0156","title":"Quantifying the impact of Russia–Ukraine crisis on food security and trade pattern: evidence from a structural general equilibrium trade model","year":2023,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"Russia and Soviet political economy","field":"Social Sciences","cited_by":58,"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":"Food security; General equilibrium theory; Economics; Agriculture; Partial equilibrium; Welfare; International trade; Food prices; Food processing; Terms of trade; International economics; Macroeconomics; Political science; Geography; Market economy","score_opus":0.0698860960407788,"score_gpt":0.3487355563781291,"score_spread":0.27884946033735025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313430432","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97093695,0.0022129114,0.012926677,0.00084827095,0.00005205929,0.00003503993,0.00037266038,0.000051788673,0.01256364],"genre_scores_gemma":[0.99776006,0.00075347663,0.0007808746,0.00003154811,0.000007888245,0.000010298588,0.00013786864,0.000006125774,0.00051195134],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995277,0.0002566031,0.00002303212,0.00006980242,0.00003904825,0.00008379639],"domain_scores_gemma":[0.9983758,0.0010813081,0.0002808443,0.000067477486,0.00013803807,0.00005651338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013740911,0.0006045486,0.00078963564,0.00080167135,0.00038660868,0.0014709543,0.00066474563,0.0005901451,0.0027838424],"category_scores_gemma":[0.0028253589,0.00025712946,0.0012239977,0.0008735162,0.00068741373,0.0010656173,0.00096789247,0.00076276076,0.00018490954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042390177,0.00022997454,0.07631634,0.00042705584,0.0010416231,0.00083438377,0.0003421076,0.83086437,0.00087133836,0.06998616,0.002268758,0.016393965],"study_design_scores_gemma":[0.00009783259,0.00036499908,0.043117847,0.0001503816,0.00076841295,0.00018529086,0.0011468154,0.89574254,0.00053802953,0.054875154,0.002960996,0.000051742212],"about_ca_topic_score_codex":0.0155199375,"about_ca_topic_score_gemma":0.007011245,"teacher_disagreement_score":0.0155199375,"about_ca_system_score_codex":0.0014647626,"about_ca_system_score_gemma":0.0011769504,"threshold_uncertainty_score":0.030859232},"labels":[],"label_agreement":null},{"id":"W4398137093","doi":"10.1108/caer-11-2022-0258","title":"Do climate disasters make farmers more willing to cooperate? Evidence from rural communities in southern China","year":2024,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","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":"Amorfix (Canada)","funders":"","keywords":"China; Business; Natural resource economics; Development economics; Socioeconomics; Agricultural economics; Economic growth; Geography; Economics","score_opus":0.039959768833825925,"score_gpt":0.28364672482706993,"score_spread":0.243686955993244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398137093","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99904984,0.0003171384,0.000024892086,0.00016817702,0.000002866834,0.0000060600937,0.000020299516,4.0303286e-7,0.00041041308],"genre_scores_gemma":[0.9994578,0.0003572375,0.000020598885,0.000050647915,0.0000040828118,0.000007119274,0.000025631842,2.68005e-7,0.00007672562],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991041,0.0004019391,0.000054076576,0.00013110835,0.00010773515,0.0002009361],"domain_scores_gemma":[0.99633896,0.0014257563,0.0013873724,0.00013814442,0.00030985154,0.0003999252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021026295,0.0002819631,0.00035093873,0.0009747159,0.00101311,0.0005842742,0.00046375062,0.00042682345,0.002063739],"category_scores_gemma":[0.0039399783,0.00018683777,0.0003692151,0.0014335233,0.0011750724,0.0007148199,0.0008945036,0.00039292162,0.00009687705],"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":[0.00015594091,0.0002834923,0.9427696,0.0005552167,0.0001489826,0.0014448644,0.035770565,0.00015418707,0.00049464236,0.0005690585,0.00055045064,0.017102987],"study_design_scores_gemma":[0.000015033422,0.00011243316,0.96523774,0.000101966805,0.00006368147,0.00010757451,0.03305893,0.00012944495,0.000047524543,0.00017951438,0.00093651377,0.000009602296],"about_ca_topic_score_codex":0.027321065,"about_ca_topic_score_gemma":0.035402317,"teacher_disagreement_score":0.027321065,"about_ca_system_score_codex":0.00082774943,"about_ca_system_score_gemma":0.0018316644,"threshold_uncertainty_score":0.05432409},"labels":[],"label_agreement":null},{"id":"W4414988113","doi":"10.1108/caer-09-2024-0316","title":"Impact of implementation of high-standard farmland construction policy on food production resilience: evidence from China","year":2025,"lang":"en","type":"article","venue":"China Agricultural Economic Review","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute on Governance","funders":"China Scholarship Council; National Natural Science Foundation of China","keywords":"Safeguard; Production (economics); China; Food processing; Government (linguistics); Food security; Resilience (materials science); Agriculture; Quality (philosophy)","score_opus":0.01254161539672835,"score_gpt":0.29848521254521515,"score_spread":0.2859435971484868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414988113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99682057,0.0010028298,0.00027954706,0.00047987304,0.000016575785,0.00003420233,0.0003568209,0.000010681891,0.0009990621],"genre_scores_gemma":[0.9990382,0.0003436485,0.00011767313,0.000083019986,0.0000056170306,0.000021300588,0.00023265177,0.0000019448369,0.00015595238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99768984,0.00069239415,0.00023698212,0.00038222782,0.0004611335,0.00053742155],"domain_scores_gemma":[0.9928975,0.0016119119,0.00307492,0.00067613117,0.0009796125,0.0007598577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031269807,0.0005175168,0.0005656446,0.0012869505,0.0010054538,0.0010332676,0.0010601293,0.0005031842,0.0018613525],"category_scores_gemma":[0.0066243173,0.00023349866,0.0011009529,0.0019741734,0.002082823,0.0009214757,0.0017780116,0.00073969667,0.00011082888],"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":[0.00029718137,0.00034199623,0.9596341,0.0007236154,0.0008073568,0.0006232912,0.0020986765,0.0021498206,0.000532059,0.0023102115,0.0011677954,0.02931393],"study_design_scores_gemma":[0.00002937359,0.00018261303,0.99444395,0.00016462759,0.00024995618,0.000032332926,0.0017003609,0.0010547847,0.00021677438,0.0004027647,0.0014997778,0.000022703369],"about_ca_topic_score_codex":0.105483465,"about_ca_topic_score_gemma":0.1520915,"teacher_disagreement_score":0.105483465,"about_ca_system_score_codex":0.0040880814,"about_ca_system_score_gemma":0.007822159,"threshold_uncertainty_score":0.20973897},"labels":[],"label_agreement":null}]}