{"meta":{"query_hash":"8df3c65b8e3a","filters":{"venue":"American Journal of Climate Change"},"cohort_total":19,"direct_labels_cover":0,"predictions_cover":19,"exported":19,"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/8df3c65b8e3a","api":"https://metacan.xera.ac/api/v1/cohort?venue=American+Journal+of+Climate+Change"},"results":[{"id":"W1608410893","doi":"10.4236/ajcc.2015.43020","title":"Salinity Intrusion in Interior Coast of Bangladesh: Challenges to Agriculture in South-Central Coastal Zone","year":2015,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Tropical and Extratropical Cyclones Research","field":"Earth and Planetary Sciences","cited_by":94,"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 Waterloo","funders":"","keywords":"Salinity; Environmental science; Irrigation; Soil salinity; Hydrology (agriculture); Oceanography; Agriculture; Bay; Geology; Geography; Agronomy","score_opus":0.0574988991546638,"score_gpt":0.27722465705375315,"score_spread":0.21972575789908935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1608410893","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":[0.97393227,0.001624315,0.00060087105,0.004647715,0.00003341904,0.000053180716,0.0003900338,0.000020070604,0.018698128],"genre_scores_gemma":[0.9945005,0.002827842,0.0004484095,0.00031622217,0.0000120306595,0.000017662824,0.00013874641,0.0000040572727,0.0017345716],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996278,0.00011071308,0.00003057532,0.00004263528,0.000078508376,0.000109698965],"domain_scores_gemma":[0.99942565,0.00008448333,0.00016810346,0.000025267407,0.0001828718,0.00011360573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033822813,0.00031535845,0.00020690267,0.00044662796,0.0011262327,0.0016332375,0.0003268378,0.00050282007,0.0022725002],"category_scores_gemma":[0.0006092887,0.00015864498,0.00017476799,0.0012295446,0.00082680304,0.001021475,0.001233782,0.00045437744,0.0003944816],"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":[0.00029011522,0.00019753448,0.7663801,0.0014112758,0.00012663999,0.01876701,0.02830111,0.0031873032,0.053293563,0.0054095425,0.008117922,0.11451788],"study_design_scores_gemma":[0.000023958106,0.00049529684,0.7265755,0.0005059228,0.00007918826,0.0052899956,0.20090182,0.0018172147,0.0034375596,0.0040719598,0.056695197,0.00010642155],"about_ca_topic_score_codex":0.026343621,"about_ca_topic_score_gemma":0.053995173,"teacher_disagreement_score":0.026343621,"about_ca_system_score_codex":0.0013476156,"about_ca_system_score_gemma":0.0018218507,"threshold_uncertainty_score":0.05238056},"labels":[],"label_agreement":null},{"id":"W2032322156","doi":"10.4236/ajcc.2014.32013","title":"Impact of Climate Change and Variability on Wheat and Corn Production in Buenos Aires, Argentina","year":2014,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Climate variability and models","field":"Environmental Science","cited_by":6,"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 Winnipeg","funders":"","keywords":"Teleconnection; Precipitation; La Niña; Climatology; El Niño Southern Oscillation; Environmental science; Arctic oscillation; Climate change; Atmospheric sciences; Agronomy; Geography; Oceanography; Biology; Geology; Meteorology","score_opus":0.03602973010632555,"score_gpt":0.2794134596141527,"score_spread":0.24338372950782716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032322156","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":[0.9950435,0.00046803,0.00015479852,0.00028949862,0.000017519125,0.000007430264,0.0021235272,0.000028778628,0.0018667734],"genre_scores_gemma":[0.9973431,0.00039155208,0.00012477172,0.000014334281,0.000013586239,0.000010222915,0.0016092209,0.000006854523,0.00048630443],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982363,0.000051249477,0.000011262848,0.000044954224,0.00003155104,0.00003735319],"domain_scores_gemma":[0.99972445,0.00006692324,0.000085936386,0.000012695918,0.00005811742,0.000051846167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033744946,0.00032169407,0.00020707794,0.00043104147,0.00023102973,0.0006974632,0.00023380232,0.00021696235,0.0014929099],"category_scores_gemma":[0.00063773163,0.000130934,0.00024806234,0.0006924444,0.00018666666,0.0002637518,0.00028052827,0.00021268569,0.00016294447],"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":[0.00045623264,0.00014496144,0.9632731,0.00009531978,0.00017655028,0.00047105204,0.0002179527,0.016420884,0.0023387852,0.00095182896,0.0030844037,0.012368935],"study_design_scores_gemma":[0.000036207643,0.000043423945,0.9865246,0.0000135129285,0.000026193047,0.000053734646,0.00019649715,0.0113066,0.00013453631,0.00013443576,0.001522555,0.0000075859016],"about_ca_topic_score_codex":0.16911134,"about_ca_topic_score_gemma":0.17623097,"teacher_disagreement_score":0.16911134,"about_ca_system_score_codex":0.0016943412,"about_ca_system_score_gemma":0.0004972929,"threshold_uncertainty_score":0.336254},"labels":[],"label_agreement":null},{"id":"W2062344118","doi":"10.4236/ajcc.2013.24027","title":"Climate Change Effect on Winter Temperature and Precipitation of Yellowknife, Northwest Territories, Canada from 1943 to 2011","year":2013,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Climate variability and models","field":"Environmental Science","cited_by":28,"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 Winnipeg","funders":"","keywords":"Precipitation; Climatology; Negative correlation; Pacific decadal oscillation; La Niña; Positive correlation; Environmental science; Arctic oscillation; Atmospheric sciences; El Niño Southern Oscillation; North Atlantic oscillation; Geology; Geography; Meteorology","score_opus":0.011229866011644614,"score_gpt":0.22231155038502914,"score_spread":0.21108168437338454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062344118","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":[0.9878721,0.0006409764,0.00006440815,0.00027281063,0.000031221552,0.000008576541,0.009257931,0.000014672347,0.0018371806],"genre_scores_gemma":[0.9902192,0.00073843496,0.0001692251,0.000071033624,0.000013304352,0.000015247303,0.006257114,0.00000843075,0.002507947],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997564,0.000016009206,0.00002001298,0.00005289681,0.00006895131,0.000085635766],"domain_scores_gemma":[0.9987923,0.000057052155,0.00021238586,0.00003695802,0.0006554569,0.0002458307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003487118,0.0002975735,0.00029465076,0.00066406175,0.0012537977,0.0011031091,0.00041500395,0.00026419526,0.0011472922],"category_scores_gemma":[0.0012395597,0.00019737332,0.0004950456,0.0024178848,0.00038974133,0.000265226,0.0005558671,0.00047537623,0.00017783973],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078139776,0.000011664747,0.99537295,0.000022124574,0.00008716224,0.00008730866,0.00025694867,0.00044131378,0.00031274187,0.00006096411,0.0009496075,0.002319143],"study_design_scores_gemma":[0.0000025482657,0.0000037314078,0.9986248,0.0000070225,0.000010688353,0.000022522934,0.00025992398,0.00014494361,0.000049270955,0.000005070152,0.0008662997,0.0000032822393],"about_ca_topic_score_codex":0.9859941,"about_ca_topic_score_gemma":0.9939673,"teacher_disagreement_score":0.014005899,"about_ca_system_score_codex":0.012770472,"about_ca_system_score_gemma":0.017112974,"threshold_uncertainty_score":0.09265673},"labels":[],"label_agreement":null},{"id":"W2133955003","doi":"10.4236/ajcc.2014.33026","title":"Trend and Periodicity of Temperature Time Series in Ontario","year":2014,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Climate variability and models","field":"Environmental Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Government of Manitoba; University of Guelph","funders":"","keywords":"Trend analysis; Environmental science; Climatology; Maximum temperature; Mean radiant temperature; Series (stratigraphy); Climate change; Atmospheric sciences; Geology; Statistics; Mathematics; Oceanography","score_opus":0.014586223396003364,"score_gpt":0.22011226891208235,"score_spread":0.205526045516079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133955003","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":[0.99167836,0.00039984452,0.00033505034,0.00014248767,0.000006822965,0.000010853353,0.002846307,0.00002090842,0.0045594103],"genre_scores_gemma":[0.99553114,0.0003101633,0.0003059855,0.000011477395,0.000004309819,0.000008432037,0.0015469613,0.0000063805032,0.0022753058],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996735,0.000016261392,0.00002246794,0.00006698508,0.00015580337,0.000064964304],"domain_scores_gemma":[0.9989359,0.00009617597,0.0002681579,0.000041815583,0.00058413204,0.00007387357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023857741,0.00011126939,0.0001723729,0.0011024404,0.0006743997,0.0007160082,0.00024676282,0.000113680224,0.0011259537],"category_scores_gemma":[0.0016667871,0.00016590332,0.00019009277,0.0032894693,0.00031563215,0.00027741084,0.00034923095,0.00013157856,0.00013030066],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000117988166,0.000009246908,0.9753852,0.00008691567,0.00007796601,0.00017992489,0.0021587529,0.0016655811,0.002133216,0.0003893775,0.0015544859,0.016241377],"study_design_scores_gemma":[0.000001917835,0.000005209851,0.997083,0.0000055023693,0.0000074724603,0.000015934636,0.0002812998,0.00061225484,0.00009385952,0.000027784641,0.0018619975,0.0000037287105],"about_ca_topic_score_codex":0.93461823,"about_ca_topic_score_gemma":0.97022927,"teacher_disagreement_score":0.065381765,"about_ca_system_score_codex":0.008009402,"about_ca_system_score_gemma":0.0058609666,"threshold_uncertainty_score":0.13153356},"labels":[],"label_agreement":null},{"id":"W2146651957","doi":"10.4236/ajcc.2013.21007","title":"Hydro-Meteorological Trends in Southwest Coastal Bangladesh: Perspectives of Climate Change and Human Interventions","year":2013,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Environmental science; Hydrology (agriculture); Climate change; Sunshine duration; Brackish water; Salinity; Relative humidity; Geography; Oceanography; Meteorology; Geology","score_opus":0.040441691054832966,"score_gpt":0.30377975085784636,"score_spread":0.2633380598030134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146651957","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":[0.96134806,0.007322559,0.00021628884,0.012706469,0.00009299948,0.000031485284,0.004144615,0.000017061777,0.0141202435],"genre_scores_gemma":[0.9946957,0.004057388,0.00006445541,0.00026193543,0.000035099252,0.000015703705,0.00036961932,0.000001713209,0.0004983888],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99972576,0.00012634291,0.000023684092,0.000020551563,0.000021482198,0.00008217952],"domain_scores_gemma":[0.9993781,0.00008986192,0.00020853529,0.00001687808,0.000110551235,0.00019614266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037099107,0.000116579904,0.0001446814,0.0008269054,0.0004190371,0.0008314284,0.00015691876,0.00034365922,0.003389213],"category_scores_gemma":[0.0010925266,0.00007572034,0.00020088191,0.0021093856,0.0003341298,0.000586416,0.0005188467,0.00033617983,0.00020526392],"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":[0.0001384847,0.00008798939,0.9600593,0.0002847134,0.00008410022,0.00077242113,0.0031295114,0.00036640296,0.00057823875,0.0020847276,0.0028993653,0.02951492],"study_design_scores_gemma":[0.0000033523868,0.00005678667,0.9868455,0.00007298204,0.000016169774,0.00014947304,0.00814333,0.0001752756,0.000049692873,0.00022232137,0.004256032,0.000009092211],"about_ca_topic_score_codex":0.037371676,"about_ca_topic_score_gemma":0.061381184,"teacher_disagreement_score":0.037371676,"about_ca_system_score_codex":0.0011374858,"about_ca_system_score_gemma":0.0013823997,"threshold_uncertainty_score":0.074308276},"labels":[],"label_agreement":null},{"id":"W2313085328","doi":"10.4236/ajcc.2016.51012","title":"Uncertainty in Precipitation Projection under Changing Climate Conditions: A Regional Case Study","year":2016,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Climate variability and models","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Downscaling; Precipitation; Environmental science; Climatology; Representative Concentration Pathways; GCM transcription factors; Greenhouse gas; Climate change; Metric (unit); Drainage basin; Climate model; Uncertainty analysis; General Circulation Model; Meteorology; Statistics; Mathematics; Geology; Geography","score_opus":0.0612105255914961,"score_gpt":0.3228802161309764,"score_spread":0.2616696905394803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2313085328","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":[0.9910183,0.00022606751,0.005131077,0.00033635908,0.0000049146493,0.00002940542,0.0007364793,0.00004002773,0.0024773763],"genre_scores_gemma":[0.99732924,0.00009420916,0.0022170425,0.000010927583,0.000003291605,0.000006969942,0.00020226376,0.000005964699,0.00013006903],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985948,0.000704689,0.00005257358,0.00018467219,0.0003274681,0.00013568392],"domain_scores_gemma":[0.9965043,0.0024610837,0.00026443953,0.00018606392,0.0005080327,0.000075999116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026054718,0.0003337134,0.00038349812,0.00068185764,0.0006450932,0.0011692747,0.00085948844,0.0006645692,0.0004933279],"category_scores_gemma":[0.0065586516,0.00020651893,0.00056033547,0.002083178,0.00059576554,0.0006258511,0.0006641074,0.0006818466,0.000038890106],"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":[0.00017793411,0.000043768116,0.06055748,0.00006258549,0.00018177436,0.0009453106,0.00029236556,0.9222708,0.0009637061,0.00221807,0.0005646331,0.011721588],"study_design_scores_gemma":[0.000061468054,0.00014018518,0.10884697,0.00005505045,0.00021321897,0.00034937126,0.001550449,0.88012004,0.0029564735,0.00281876,0.002788446,0.000099556935],"about_ca_topic_score_codex":0.3582823,"about_ca_topic_score_gemma":0.36013246,"teacher_disagreement_score":0.3582823,"about_ca_system_score_codex":0.004146177,"about_ca_system_score_gemma":0.0020300227,"threshold_uncertainty_score":0.71239376},"labels":[],"label_agreement":null},{"id":"W2551806302","doi":"10.4236/ajcc.2016.54036","title":"Global Climate Model Selection for Analysis of Uncertainty in Climate Change Impact Assessments of Hydro-Climatic Extremes","year":2016,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Climate variability and models","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Climate change; Environmental science; Percentile; Climate model; Downscaling; Quantile; Climatology; Precipitation; Climate change scenario; Range (aeronautics); Streamflow; Baseline (sea); Econometrics; Meteorology; Drainage basin; Statistics; Mathematics; Geography","score_opus":0.06895552185753083,"score_gpt":0.3616449550573484,"score_spread":0.29268943319981755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551806302","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":[0.34927633,0.00045743078,0.63364816,0.00031074026,0.0000681496,0.00046344468,0.006252251,0.0029706475,0.0065529244],"genre_scores_gemma":[0.8270146,0.00022783743,0.16250905,0.00009036769,0.000027232407,0.00057002157,0.008038949,0.00043530815,0.0010866262],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989011,0.00076123845,0.00003537919,0.000076512464,0.00017125538,0.000054494827],"domain_scores_gemma":[0.9960794,0.0031739792,0.0001781827,0.00024758634,0.00028161818,0.000039139788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004992812,0.0007199198,0.00061515253,0.0012787196,0.00044190578,0.0005649824,0.00055558345,0.00036630852,0.0024397923],"category_scores_gemma":[0.008656441,0.0002709851,0.0011113299,0.0013748712,0.0002010007,0.0004956278,0.00056894234,0.0007257212,0.00030312478],"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":[0.00019079224,0.000060323207,0.015478989,0.00005108405,0.00023021092,0.00012199994,0.000054559354,0.9333567,0.001183181,0.0028192722,0.0022912293,0.044161696],"study_design_scores_gemma":[0.00002122767,0.000028277835,0.004901359,0.0000099761255,0.000023820683,0.000017213379,0.00001903426,0.99133486,0.0009590786,0.0017869459,0.0008868924,0.000011334852],"about_ca_topic_score_codex":0.008676986,"about_ca_topic_score_gemma":0.007693499,"teacher_disagreement_score":0.008676986,"about_ca_system_score_codex":0.00042341303,"about_ca_system_score_gemma":0.00089548377,"threshold_uncertainty_score":0.026404858},"labels":[],"label_agreement":null},{"id":"W2776056334","doi":"10.4236/ajcc.2017.64034","title":"Climate Change Induced Vulnerability of Smallholder Farmers: Agroecology-Based Analysis in the Muger Sub-Basin of the Upper Blue-Nile Basin of Ethiopia","year":2017,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Addis Ababa University; Deutscher Akademischer Austauschdienst; International Development Research Centre","keywords":"Agroecology; Livelihood; Adaptive capacity; Vulnerability (computing); Climate change; Food security; Geography; Agriculture; Agricultural diversification; Diversification (marketing strategy); Vulnerability assessment; Social vulnerability; Capital asset; Agroforestry; Socioeconomics; Environmental science; Business; Ecology; Psychological resilience; Economics","score_opus":0.0765137580637811,"score_gpt":0.3063619163344185,"score_spread":0.2298481582706374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2776056334","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":[0.9995278,0.000034591405,0.000056547626,0.000027437012,6.618361e-7,0.000011526714,0.00006448741,4.2689882e-7,0.0002764734],"genre_scores_gemma":[0.9997031,0.00004703659,0.00006916173,0.00001135864,8.767936e-7,0.000012513309,0.000049316302,4.195851e-7,0.00010615327],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996352,0.0001320548,0.000023385895,0.000049580376,0.000054791308,0.00010490372],"domain_scores_gemma":[0.99915063,0.00033369075,0.0002314576,0.00002779933,0.00011199253,0.0001444573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005474036,0.00021306849,0.00023521297,0.0015601105,0.00091001194,0.0009793773,0.00035447895,0.00036221193,0.0014120532],"category_scores_gemma":[0.001351155,0.00014121138,0.0002840959,0.0016155929,0.0007632704,0.0007739408,0.001084547,0.0003147577,0.000117174925],"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":[0.000069005226,0.00011811806,0.9670314,0.000085400214,0.000071336246,0.0019686061,0.022528796,0.0005068099,0.0016426984,0.0003111337,0.00016915081,0.0054976065],"study_design_scores_gemma":[0.000002125413,0.000089839574,0.934217,0.000033581902,0.00001879582,0.00035159983,0.06376045,0.0006173086,0.00017687856,0.00020307115,0.0005196445,0.000009736758],"about_ca_topic_score_codex":0.01135893,"about_ca_topic_score_gemma":0.020698847,"teacher_disagreement_score":0.01135893,"about_ca_system_score_codex":0.0010087923,"about_ca_system_score_gemma":0.0005640268,"threshold_uncertainty_score":0.02258563},"labels":[],"label_agreement":null},{"id":"W2807954657","doi":"10.4236/ajcc.2018.72017","title":"Early 20&amp;lt;sup&amp;gt;th&amp;lt;/sup&amp;gt; Century Climate-Driven Shift in the Dynamics of Forest Tent Caterpillar Outbreaks","year":2018,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":14,"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 Alberta; Natural Resources Canada","funders":"National Oceanic and Atmospheric Administration","keywords":"Synchronizing; Environmental science; Atmospheric sciences; Climate change; Ecology; Population; Climatology; Biology; Physics; Geology; Demography; Mathematics","score_opus":0.017391536049130567,"score_gpt":0.24920120070454582,"score_spread":0.23180966465541525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807954657","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":[0.9957547,0.00014556407,0.00032647696,0.00007857057,0.0000063632965,0.0000032070138,0.00041503264,0.000013932093,0.0032559857],"genre_scores_gemma":[0.998966,0.000083871906,0.000120484714,0.000011827637,0.0000038627354,0.0000012040693,0.0002330164,0.0000024754981,0.00057733327],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99995863,0.0000040744853,0.0000018797434,0.000009217,0.000012396361,0.000013785331],"domain_scores_gemma":[0.99979955,0.000014959229,0.00006788091,0.000011666893,0.000063574145,0.000042398406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018015507,0.00007883291,0.000058800775,0.00062067073,0.00029137646,0.0005149475,0.00017450641,0.00014664352,0.001959108],"category_scores_gemma":[0.00052304607,0.000053699958,0.000094582225,0.00045104977,0.00037007,0.00013754652,0.00024479395,0.00015352081,0.00012820742],"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":[0.00019366258,0.000029086877,0.9615709,0.00003107218,0.00004231212,0.00031776272,0.0007355325,0.0038496738,0.009421669,0.0018108166,0.0013456327,0.020651894],"study_design_scores_gemma":[0.0000018183218,0.000005231947,0.99744415,0.0000034657028,0.0000049522278,0.00003137202,0.000101674625,0.0008740206,0.0003219807,0.00008834849,0.0011202046,0.0000028334084],"about_ca_topic_score_codex":0.32325578,"about_ca_topic_score_gemma":0.5197582,"teacher_disagreement_score":0.32325578,"about_ca_system_score_codex":0.0020153383,"about_ca_system_score_gemma":0.00080703053,"threshold_uncertainty_score":0.6427485},"labels":[],"label_agreement":null},{"id":"W2886172076","doi":"10.4236/ajcc.2018.73024","title":"Relating Fish Hg to Variations in Sediment Hg, Climate and Atmospheric Deposition","year":2018,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"Environment and Climate Change Canada","keywords":"Environmental science; Perch; Methylmercury; Climate change; Sediment; Mercury (programming language); Subarctic climate; Fish <Actinopterygii>; Permafrost; Hydrology (agriculture); Bioaccumulation; Environmental chemistry; Fishery; Oceanography; Geology; Chemistry; Biology","score_opus":0.022660323868166136,"score_gpt":0.2829411746817859,"score_spread":0.2602808508136198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886172076","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":[0.99629503,0.00031212656,0.00062066613,0.000055121516,0.0000062229483,0.0000088107245,0.0014375817,0.00001603025,0.0012485086],"genre_scores_gemma":[0.9974638,0.00024350632,0.00045958345,0.00002639552,0.000008456064,0.000009470487,0.0009908115,0.000007788427,0.00079018256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982435,0.000028054976,0.000011182702,0.00006325749,0.00003994976,0.000033277498],"domain_scores_gemma":[0.9996238,0.00009014239,0.00012110024,0.000032787884,0.000089267065,0.000042906766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031609196,0.00029378035,0.00011146054,0.0007299157,0.00019000434,0.00029830608,0.0001765873,0.00020703628,0.0012864107],"category_scores_gemma":[0.0008823625,0.0001556356,0.00028056063,0.0011245384,0.0002153359,0.00021821543,0.00031797375,0.00019144683,0.0002468647],"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":[0.000047597794,0.000008295721,0.9932853,0.000011253317,0.00011042213,0.000032728396,0.000032665474,0.0013479644,0.001450319,0.00003148396,0.00011012787,0.003531815],"study_design_scores_gemma":[7.6188763e-7,0.000023136623,0.99850625,0.0000014903412,0.00002058915,0.00002140635,0.00003864083,0.0008550406,0.0002566618,0.00004120185,0.00023253186,0.0000020849686],"about_ca_topic_score_codex":0.08392596,"about_ca_topic_score_gemma":0.09438172,"teacher_disagreement_score":0.08392596,"about_ca_system_score_codex":0.00095490087,"about_ca_system_score_gemma":0.0004850395,"threshold_uncertainty_score":0.16687495},"labels":[],"label_agreement":null},{"id":"W2900101493","doi":"10.4236/ajcc.2018.74035","title":"Impacts of Climate Change on Seasonal Residential Electricity Consumption by 2050 and Potential Adaptation Options in Alexandria Egypt","year":2018,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Alexandria University; International Development Research Centre","keywords":"Electricity; Consumption (sociology); Climate change; Environmental science; Seasonality; Population; Agricultural economics; Geography; Ecology; Economics; Environmental health; Engineering; Medicine; Biology","score_opus":0.03168617066426329,"score_gpt":0.29335786174133566,"score_spread":0.2616716910770724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900101493","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":[0.9963612,0.00016985046,0.0002538601,0.00024119952,0.0000041643398,0.000006324145,0.00073612825,0.000010505955,0.002216785],"genre_scores_gemma":[0.99860555,0.00016446674,0.00014132519,0.000021757498,0.0000017440883,0.0000047867497,0.0004367673,0.0000017360135,0.0006218294],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999019,0.000024044968,0.000006078233,0.000013243051,0.000016150712,0.000038657403],"domain_scores_gemma":[0.999913,0.000018685596,0.000021541882,0.000006202737,0.000030699,0.000009786609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022617524,0.0001727179,0.00015389016,0.0003375481,0.00021572737,0.00074624334,0.00029390643,0.00037206316,0.0011018504],"category_scores_gemma":[0.0002515535,0.00012304878,0.00046432344,0.0008167883,0.00017217924,0.00034920598,0.00037998214,0.00026553974,0.00011492788],"study_design_candidate":"simulation_or_modeling","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":[0.0005607544,0.00019826366,0.7613925,0.00026311976,0.0004916701,0.0027318525,0.00086480315,0.1860212,0.0071165273,0.0042329216,0.0038328907,0.032293554],"study_design_scores_gemma":[0.000021286613,0.0001256825,0.9090015,0.000067914916,0.0001636076,0.0001892342,0.0036338263,0.07824308,0.0025101516,0.00063438405,0.005369777,0.000039522874],"about_ca_topic_score_codex":0.10395947,"about_ca_topic_score_gemma":0.1618317,"teacher_disagreement_score":0.10395947,"about_ca_system_score_codex":0.002656826,"about_ca_system_score_gemma":0.00096766336,"threshold_uncertainty_score":0.20670873},"labels":[],"label_agreement":null},{"id":"W2973415810","doi":"10.4236/ajcc.2019.83021","title":"Modeling Reforestation’s Role in Climate-Proofing Watersheds from Flooding and Soil Erosion","year":2019,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Manitoba; Dalhousie University","funders":"Agriculture and Agri-Food Canada","keywords":"Reforestation; Environmental science; Flooding (psychology); Erosion; Watershed; Surface runoff; Hydrology (agriculture); Riparian zone; Buffer strip; Climate change; Agroforestry; Water resource management; Habitat; Ecology; Geology","score_opus":0.025088921107836757,"score_gpt":0.22767095517901453,"score_spread":0.20258203407117778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973415810","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":[0.99784434,0.00003300925,0.0007609003,0.000055368422,0.0000023463845,0.000016758278,0.00012304903,0.000012769297,0.0011514644],"genre_scores_gemma":[0.99886346,0.000030362991,0.0005744195,0.0000053627405,0.0000012917784,0.0000074329055,0.00007146837,0.000002343561,0.00044394238],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998734,0.000037397607,0.0000046712894,0.000025331532,0.00001107569,0.000048106755],"domain_scores_gemma":[0.999582,0.00020925744,0.000068306705,0.000017511506,0.000050064744,0.00007286851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040537276,0.00033622968,0.00022024612,0.00030252256,0.00040117517,0.00094371184,0.00084806344,0.00077759457,0.0008717556],"category_scores_gemma":[0.0011833784,0.00029507105,0.00033187575,0.00031970793,0.000476386,0.00048174956,0.00034973057,0.00036063886,0.00005718514],"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":[0.000105430256,0.00009450121,0.04739241,0.000021396834,0.0000314601,0.00013392587,0.00006787402,0.9480318,0.0012668684,0.0009677344,0.000090532754,0.0017961293],"study_design_scores_gemma":[0.000024254972,0.00006299234,0.023548797,0.000006261497,0.000021701868,0.000019124727,0.00009554279,0.975226,0.0003661726,0.0004159854,0.00020393213,0.000009257176],"about_ca_topic_score_codex":0.34273407,"about_ca_topic_score_gemma":0.4178893,"teacher_disagreement_score":0.34273407,"about_ca_system_score_codex":0.0029182464,"about_ca_system_score_gemma":0.0028611273,"threshold_uncertainty_score":0.68147826},"labels":[],"label_agreement":null},{"id":"W2992563900","doi":"10.4236/ajcc.2019.84029","title":"Hudson Bay Climate Change and Local Winter Wind Circulation","year":2019,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University","funders":"National Oceanic and Atmospheric Administration","keywords":"Bay; Anomaly (physics); Climatology; Wind speed; Westerlies; Geology; Albedo (alchemy); Environmental science; Atmospheric sciences; Jet stream; Wind direction; Oceanography; Jet (fluid)","score_opus":0.02165443952210043,"score_gpt":0.2326341811679824,"score_spread":0.21097974164588196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2992563900","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":[0.99195963,0.00038216627,0.00003875562,0.00018582042,0.000035465397,0.0000057290076,0.004407473,0.000023505196,0.0029614242],"genre_scores_gemma":[0.99544525,0.00030961848,0.000071207905,0.000045501572,0.000018242205,0.0000057537895,0.0025009082,0.000004874105,0.0015986942],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9999058,0.000010215457,0.000008400899,0.000028408305,0.000016747319,0.000030570554],"domain_scores_gemma":[0.99967325,0.000022318636,0.00011140232,0.000019986388,0.000077333665,0.000095665506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018560956,0.00017423455,0.00015126707,0.00071704306,0.00025541373,0.00095352676,0.00020644176,0.00013519076,0.0035058667],"category_scores_gemma":[0.00052943936,0.00008843986,0.00015178374,0.001242548,0.00022606655,0.0003230864,0.00049956003,0.00020823581,0.00029738148],"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":[0.000056437246,0.000016662434,0.9878935,0.000038356564,0.00006345992,0.00026459893,0.00034952734,0.0005405308,0.0005716215,0.00016584397,0.0032864085,0.0067530186],"study_design_scores_gemma":[0.0000020905732,0.0000069735443,0.9980806,0.000009250276,0.000005678065,0.000015977132,0.0003915921,0.00014575054,0.000035723977,0.000014216236,0.0012900634,0.0000020384891],"about_ca_topic_score_codex":0.30004707,"about_ca_topic_score_gemma":0.42301443,"teacher_disagreement_score":0.30004707,"about_ca_system_score_codex":0.001873834,"about_ca_system_score_gemma":0.00089517666,"threshold_uncertainty_score":0.59660125},"labels":[],"label_agreement":null},{"id":"W4205717678","doi":"10.4236/ajcc.2021.104024","title":"Investigation of Long-Term Climate and Streamflow Patterns in Ontario","year":2021,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Streamflow; Baseflow; Snowmelt; Precipitation; Climate change; Environmental science; Surface runoff; Climatology; Snow; Geography; Physical geography; Drainage basin; Hydrology (agriculture); Meteorology; Geology","score_opus":0.02857594240205534,"score_gpt":0.24005806508460342,"score_spread":0.21148212268254807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205717678","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":[0.99612457,0.000080018785,0.00010263618,0.00006791656,0.0000026771143,0.000019434461,0.0013809284,0.00000824415,0.0022135866],"genre_scores_gemma":[0.9959875,0.00019129549,0.00026269915,0.000028383794,0.0000033693268,0.000023121462,0.0012872603,0.000004327382,0.0022122131],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998091,0.000009338633,0.000010175987,0.000042003277,0.00007367657,0.000055762543],"domain_scores_gemma":[0.9994885,0.000027644524,0.00010486191,0.000018266584,0.0002655744,0.00009518919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016149698,0.00015048358,0.00019235346,0.0007293021,0.0014873169,0.0006009263,0.00038164976,0.0001669354,0.0009104238],"category_scores_gemma":[0.00056575594,0.00013994599,0.00023678217,0.0025059257,0.0003463043,0.00024124383,0.000418737,0.00017659453,0.000119881515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077826684,0.00003878284,0.98247725,0.000045787307,0.000037168982,0.00031351953,0.0030611951,0.0003551741,0.0026829247,0.00014684224,0.0008920394,0.009871604],"study_design_scores_gemma":[0.00000152941,0.000009677155,0.9973527,0.0000047394346,0.0000060711327,0.000021454292,0.0009564983,0.0002436627,0.00008329085,0.000012876351,0.0013038849,0.0000036092083],"about_ca_topic_score_codex":0.96793383,"about_ca_topic_score_gemma":0.99076045,"teacher_disagreement_score":0.032066166,"about_ca_system_score_codex":0.011752197,"about_ca_system_score_gemma":0.011778131,"threshold_uncertainty_score":0.08526862},"labels":[],"label_agreement":null},{"id":"W4382724488","doi":"10.4236/ajcc.2023.122014","title":"Analysis of Weather Anomalies to Assess the 2021 Flood Events in Yaounde, Cameroon (Central Africa)","year":2023,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Agence Universitaire de la Francophonie; Institut de Recherche pour le Développement","keywords":"Precipitation; Environmental science; Climatology; Flood myth; Dew point; Relative humidity; Dry season; Wind speed; Geography; Meteorology; Cartography; Geology","score_opus":0.03690937793667249,"score_gpt":0.28588898466836155,"score_spread":0.24897960673168906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382724488","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":[0.996296,0.00010361812,0.00031683294,0.00005367554,0.000008998383,0.000026953747,0.0025324663,0.000015862708,0.0006455175],"genre_scores_gemma":[0.9965837,0.00011590598,0.00070487463,0.000009701921,0.0000083371315,0.000046797257,0.0022868188,0.0000026421103,0.00024130999],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980706,0.00005232444,0.000025270012,0.00003194039,0.00003501515,0.000048382833],"domain_scores_gemma":[0.9994874,0.0001386661,0.00015468539,0.000020790445,0.00014726777,0.0000512468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006102258,0.0003391409,0.00019932922,0.0022138592,0.00028273163,0.00058640924,0.00013791912,0.0001906915,0.0008891238],"category_scores_gemma":[0.0011237346,0.000091530565,0.0001903939,0.0026256246,0.00014850774,0.0003153362,0.0002634525,0.0002219082,0.00010314677],"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":[0.0001411346,0.000059282993,0.96675336,0.00008799886,0.00008148178,0.0007342641,0.00072096573,0.00784687,0.0026328708,0.00034782325,0.0012903793,0.01930357],"study_design_scores_gemma":[0.0000042623496,0.00004084824,0.98745686,0.000024421064,0.000023352954,0.00010610172,0.0014780659,0.008861264,0.000428362,0.000056784687,0.0015090763,0.0000105928275],"about_ca_topic_score_codex":0.02560811,"about_ca_topic_score_gemma":0.02903262,"teacher_disagreement_score":0.02560811,"about_ca_system_score_codex":0.0006210716,"about_ca_system_score_gemma":0.0004662412,"threshold_uncertainty_score":0.050918162},"labels":[],"label_agreement":null},{"id":"W4386106426","doi":"10.4236/ajcc.2023.123017","title":"Are Polyploid Species Less Vulnerable to Climate Change? A Simulation Study in North American &amp;lt;i&amp;gt;Crataegus&amp;lt;/i&amp;gt;","year":2023,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Climate change; Polyploid; Range (aeronautics); Crataegus; Biology; Ecology; Ploidy; Trait; Species distribution; Genetics","score_opus":0.08357024147787373,"score_gpt":0.3238254320466484,"score_spread":0.24025519056877465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386106426","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":[0.9990087,0.000046381356,0.00019087979,0.00010005998,0.0000028915401,0.0000033021922,0.00012485059,0.0000067490364,0.00051626243],"genre_scores_gemma":[0.9992262,0.000050169063,0.00025542182,0.000025291389,0.0000014997155,0.000006172339,0.00020694021,0.0000043000546,0.00022395041],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998933,0.000034577995,0.0000045600377,0.000033621254,0.000007130416,0.00002677868],"domain_scores_gemma":[0.9995303,0.00019030095,0.00008013868,0.000040069852,0.00005699074,0.00010224071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037164663,0.00023533184,0.000277667,0.00039802675,0.0004989274,0.00063071755,0.0005601838,0.0005604978,0.0016810489],"category_scores_gemma":[0.000995487,0.00016457574,0.00061454315,0.00057437434,0.00036841276,0.00067435537,0.00033943055,0.00039576454,0.00011287474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007045226,0.0005859806,0.49123845,0.00013270989,0.00046861172,0.0011287438,0.0006461497,0.48182544,0.004907446,0.003566984,0.0035391313,0.011255845],"study_design_scores_gemma":[0.00015815163,0.00024714848,0.26195976,0.000023707667,0.00017286008,0.00018560553,0.0016914807,0.7305097,0.00063410023,0.0016001274,0.0027606885,0.00005674519],"about_ca_topic_score_codex":0.11681342,"about_ca_topic_score_gemma":0.1401388,"teacher_disagreement_score":0.8831866,"about_ca_system_score_codex":0.0014271112,"about_ca_system_score_gemma":0.00061989034,"threshold_uncertainty_score":0.23226696},"labels":[],"label_agreement":null},{"id":"W4390232005","doi":"10.4236/ajcc.2023.124030","title":"Effect of Temperature on Frost-Free Days and Length of Crop Growing Season across Southern Ontario","year":2023,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Climate variability and models","field":"Environmental Science","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":"McGill University; University of Guelph","funders":"","keywords":"Frost (temperature); Climate change; Temperate climate; Growing season; Precipitation; Environmental science; Climatology; Snow; Atmospheric sciences; Agronomy; Geography; Biology; Ecology; Geology; Meteorology","score_opus":0.01880870737631685,"score_gpt":0.2689342052111156,"score_spread":0.25012549783479876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390232005","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":[0.9966838,0.00012537866,0.000083364626,0.00008761895,0.000003026752,0.0000054496454,0.0008180142,0.000010858077,0.0021825728],"genre_scores_gemma":[0.99840975,0.00008080896,0.000048219463,0.000007909206,0.0000012457739,0.000003018595,0.0003403505,0.000003661156,0.0011049958],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998417,0.000016205418,0.00000652524,0.000036760863,0.000042838998,0.00005602241],"domain_scores_gemma":[0.9994228,0.00010396761,0.00011646087,0.00002582276,0.00018912462,0.00014182432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015998147,0.00015832295,0.00022330371,0.0002997898,0.0008325811,0.00060937816,0.00034867256,0.00016605035,0.0017863035],"category_scores_gemma":[0.0010505399,0.00014015645,0.00029330878,0.00074546045,0.0003594115,0.0001944012,0.00030958522,0.0001724436,0.000117457406],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035707687,0.00002508336,0.9810734,0.000063069056,0.0001347641,0.00024399458,0.0015091475,0.0048364503,0.005241398,0.00025511152,0.0009830854,0.0052774083],"study_design_scores_gemma":[0.0000036377883,0.000009449573,0.99786514,0.0000042318616,0.000012712758,0.000012421644,0.00044962027,0.0008589129,0.00009201797,0.000020284962,0.000667648,0.000003907186],"about_ca_topic_score_codex":0.9762359,"about_ca_topic_score_gemma":0.99128246,"teacher_disagreement_score":0.023764074,"about_ca_system_score_codex":0.010060102,"about_ca_system_score_gemma":0.0057578054,"threshold_uncertainty_score":0.07299149},"labels":[],"label_agreement":null},{"id":"W4393389674","doi":"10.4236/ajcc.2024.131004","title":"Evaluation of Rainfall Tendency for the Twentieth Century over Indira Sagar Region in Central India","year":2024,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":0,"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 Guelph","funders":"Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Geography; History; Environmental science","score_opus":0.03342932998713263,"score_gpt":0.30039516513505726,"score_spread":0.2669658351479246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393389674","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":[0.99764854,0.00028697232,0.00013069743,0.00006547881,0.0000067703186,0.00000494586,0.0010056465,0.000021943868,0.0008289392],"genre_scores_gemma":[0.9986972,0.00019888509,0.00010945176,0.000011497316,0.0000072076514,0.0000046650207,0.0007625565,0.000002487337,0.00020611942],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998926,0.0000149114085,0.000014239656,0.00002790463,0.000023345048,0.00002707988],"domain_scores_gemma":[0.99951625,0.00006524594,0.00020497339,0.000029005192,0.00013342388,0.000051115174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026471494,0.00014303779,0.000116546005,0.0016624779,0.0002268841,0.0005996907,0.00024119415,0.00015378087,0.00045762182],"category_scores_gemma":[0.0005106411,0.00008246247,0.00017075763,0.002320495,0.00019486886,0.00025479888,0.00026963928,0.00016577792,0.00010544365],"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":[0.000038474464,0.000015135758,0.9859577,0.000055451805,0.000063183645,0.0004240326,0.0009470912,0.00082419557,0.0011239507,0.0001428182,0.00047104375,0.0099368105],"study_design_scores_gemma":[6.1331576e-7,0.000013234105,0.99807966,0.0000047079325,0.000011935625,0.00012156772,0.0005974022,0.0003741538,0.00010412189,0.000011025992,0.00067796884,0.0000035767182],"about_ca_topic_score_codex":0.029203434,"about_ca_topic_score_gemma":0.05959277,"teacher_disagreement_score":0.029203434,"about_ca_system_score_codex":0.0005253935,"about_ca_system_score_gemma":0.00042893097,"threshold_uncertainty_score":0.058066905},"labels":[],"label_agreement":null},{"id":"W4401587565","doi":"10.4236/ajcc.2024.133022","title":"Irrigated Agriculture Facing the Challenge of Climate Change: Adaptation Strategies for Farmers in the Irrigated Perimeters of M&amp;#244;le Saint-Nicolas, Haiti","year":2024,"lang":"en","type":"article","venue":"American Journal of Climate Change","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Agriculture; SAINT; Irrigated agriculture; Adaptation (eye); Climate change; Irrigation; Climate change adaptation; Environmental science; Water resource management; Agroforestry; Geography; Agricultural science; Agronomy; Archaeology; Biology; Art; Ecology","score_opus":0.1057960699895259,"score_gpt":0.30197209759629834,"score_spread":0.19617602760677244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401587565","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":[0.99829465,0.000043561915,0.00008184975,0.00040777982,0.0000029453001,0.00001877823,0.000004055686,0.0000012934187,0.0011450961],"genre_scores_gemma":[0.9983796,0.00018655493,0.00034761164,0.00012686319,0.0000023434936,0.00001986309,0.0000071980376,8.721965e-7,0.0009290268],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9996375,0.0001552512,0.000008389158,0.000028454904,0.00003093562,0.0001394978],"domain_scores_gemma":[0.99961877,0.000091532485,0.00009044557,0.000011741436,0.000042178548,0.0001453057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063546526,0.00016748226,0.00012220873,0.00020563845,0.0028670877,0.0011202241,0.00048255804,0.0006413406,0.0014366789],"category_scores_gemma":[0.00092791795,0.00013188759,0.00011617496,0.00035405692,0.0011600666,0.00069051643,0.0010479965,0.0004179892,0.00016004358],"study_design_candidate":"observational","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":[0.00016940526,0.0008061905,0.30349866,0.00028697413,0.000033553326,0.007784988,0.58737284,0.00038887575,0.023166738,0.001592986,0.0018524096,0.07304634],"study_design_scores_gemma":[0.00000691607,0.00024941508,0.14802714,0.00006764734,0.0000135723985,0.0004388833,0.84053075,0.00035004644,0.00064540276,0.000353275,0.009297036,0.000019904977],"about_ca_topic_score_codex":0.012766938,"about_ca_topic_score_gemma":0.05559451,"teacher_disagreement_score":0.012766938,"about_ca_system_score_codex":0.0010046067,"about_ca_system_score_gemma":0.0019858389,"threshold_uncertainty_score":0.02538526},"labels":[],"label_agreement":null}]}