{"meta":{"query_hash":"e87623b3f70d","filters":{"venue":"Nature Environment and Pollution Technology"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/e87623b3f70d","api":"https://metacan.xera.ac/api/v1/cohort?venue=Nature+Environment+and+Pollution+Technology"},"results":[{"id":"W2578489870","doi":"","title":"Quasi-3D numerical simulation of salinity transport for reservoir initial impoundment","year":2015,"lang":"en","type":"article","venue":"Nature Environment and Pollution Technology","topic":"Geological Modeling and Analysis","field":"Earth and Planetary 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":"University of Waterloo","funders":"","keywords":"Salinity; Hydrology (agriculture); Groundwater; Estuary; Water quality; Surface water; Geology; Environmental science; Environmental engineering; Geotechnical engineering; Oceanography","score_opus":0.021269135978253757,"score_gpt":0.257404944275638,"score_spread":0.23613580829738423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2578489870","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":[0.8572423,0.00033536405,0.11315667,0.00084152183,0.00025054446,0.00017058429,0.0019086859,0.00072141056,0.025372881],"genre_scores_gemma":[0.9814185,0.00013147088,0.014975993,0.000052258412,0.000012843754,0.000107878615,0.00044811392,0.00003967475,0.0028132203],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998653,0.000030228935,0.00000993625,0.000020747491,0.000035509383,0.000038264923],"domain_scores_gemma":[0.99965537,0.00013776256,0.000042626532,0.000020271553,0.000089331545,0.000054593213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025433506,0.0005219852,0.00047816525,0.0005277098,0.0007352498,0.0009547503,0.00085628976,0.0015302546,0.0032949662],"category_scores_gemma":[0.0008743586,0.00047836613,0.0008587484,0.0005918192,0.0007150433,0.0004327806,0.00082442677,0.0006537632,0.00022290804],"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":[0.000030170493,0.000026234313,0.0017944252,0.000015490561,0.000008498923,0.00006817127,0.00002685334,0.99560803,0.00068231474,0.0008050557,0.00016455063,0.00077010953],"study_design_scores_gemma":[0.0000064497253,0.0000061389364,0.00021511687,0.0000016089813,0.0000017869975,0.0000038661997,0.000010403548,0.9994721,0.00008315036,0.00009815266,0.000098082666,0.0000031314455],"about_ca_topic_score_codex":0.06218983,"about_ca_topic_score_gemma":0.028082218,"teacher_disagreement_score":0.06218983,"about_ca_system_score_codex":0.0010081409,"about_ca_system_score_gemma":0.0014174499,"threshold_uncertainty_score":0.12365568},"labels":[],"label_agreement":null},{"id":"W3120875142","doi":"10.46488/nept.2020.v19i05.013","title":"A New Index Contributing to an Early Warning System for Cyanobacterial Bloom Occurrence in Atlantic Canada Lakes","year":2020,"lang":"en","type":"article","venue":"Nature Environment and Pollution Technology","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","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":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Bloom; Phytoplankton; Nova scotia; Dominance (genetics); Algal bloom; Environmental science; Ecology; Trophic level; Oceanography; Geography; Biology; Nutrient; Geology","score_opus":0.0036360906718933177,"score_gpt":0.16656574930898085,"score_spread":0.16292965863708753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120875142","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":[0.95856285,0.00021096595,0.031555634,0.00016784229,0.000037802547,0.00013628576,0.0032691055,0.00072221126,0.005337266],"genre_scores_gemma":[0.98544955,0.00006115201,0.011770519,0.000016347021,0.0000062663853,0.000025109803,0.001243459,0.000014449687,0.0014132182],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99982905,0.000013202052,0.000012201265,0.000034928,0.00007909636,0.00003146995],"domain_scores_gemma":[0.999419,0.000075986965,0.00006706224,0.000025166786,0.0003405623,0.00007217805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003430901,0.0004200157,0.00024784013,0.0012458835,0.0006194563,0.0009797623,0.0004460774,0.00019403824,0.0008845735],"category_scores_gemma":[0.0016621897,0.0001215391,0.00017243372,0.0008911323,0.00025306034,0.00032678142,0.00064425456,0.000233213,0.000101806465],"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":[0.0005215527,0.00019309694,0.5848715,0.00014652305,0.00014292533,0.00017175774,0.0002762709,0.22396567,0.017483832,0.0026376527,0.004527981,0.16506132],"study_design_scores_gemma":[0.000027052627,0.00010242899,0.22354315,0.000018067398,0.00007289951,0.00006651732,0.00016318122,0.7643696,0.007622566,0.00085112615,0.0030833336,0.00008009958],"about_ca_topic_score_codex":0.75470054,"about_ca_topic_score_gemma":0.73730606,"teacher_disagreement_score":0.24529946,"about_ca_system_score_codex":0.006316561,"about_ca_system_score_gemma":0.005419621,"threshold_uncertainty_score":0.49348813},"labels":[],"label_agreement":null},{"id":"W3165975092","doi":"10.46488/nept.2021.v20i02.043","title":"Statistical Downscaling of Rainfall Under Climate Change in Krishna River Sub-basin of Andhra Pradesh, India Using Artificial Neural Network (ANN)","year":2021,"lang":"en","type":"article","venue":"Nature Environment and Pollution Technology","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":4,"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":"Downscaling; Climate change; Structural basin; Artificial neural network; Environmental science; Climatology; Geography; Physical geography; Water resource management; Geology; Oceanography; Artificial intelligence; Computer science; Geomorphology","score_opus":0.014913618804682454,"score_gpt":0.2507314066366191,"score_spread":0.23581778783193663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165975092","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":[0.9968021,0.000037639165,0.0021262066,0.00006832265,0.0000080567925,0.000009388512,0.00022573423,0.00007023745,0.00065225124],"genre_scores_gemma":[0.9974235,0.00003998063,0.002125738,0.000006813441,0.000002947513,0.000007046073,0.0002441529,0.0000045072848,0.00014531176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998884,0.000029184728,0.000013396778,0.000030602547,0.000024335432,0.000014083286],"domain_scores_gemma":[0.999723,0.00010898653,0.000053880212,0.00003313688,0.000068191555,0.0000128333595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024012101,0.00016155874,0.00014386782,0.00046244112,0.00018280114,0.0002795087,0.00032019388,0.00015227575,0.0002978173],"category_scores_gemma":[0.0007605673,0.00011371719,0.00026660875,0.0007027314,0.00016870759,0.00025090243,0.00020392238,0.0002908494,0.000059368776],"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":[0.0002133424,0.00020934551,0.28445762,0.00013099246,0.0002334977,0.0006936463,0.00043790508,0.6148512,0.010797293,0.0009043558,0.0015585102,0.085512266],"study_design_scores_gemma":[0.000016664255,0.000073077,0.30557504,0.000014843986,0.000062977626,0.00010488501,0.000248844,0.6882039,0.004408744,0.0004310077,0.000833411,0.00002655844],"about_ca_topic_score_codex":0.03588363,"about_ca_topic_score_gemma":0.043222375,"teacher_disagreement_score":0.03588363,"about_ca_system_score_codex":0.00043362053,"about_ca_system_score_gemma":0.00042346772,"threshold_uncertainty_score":0.07134956},"labels":[],"label_agreement":null},{"id":"W3167239440","doi":"10.46488/nept.2021.v20i02.034","title":"Synchrotron Based TXRF for Assessment of Treated Wastewater","year":2021,"lang":"en","type":"article","venue":"Nature Environment and Pollution Technology","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":3,"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":"Synchrotron; Wastewater; Environmental science; Environmental chemistry; Chemistry; Environmental engineering; Physics; Optics","score_opus":0.008065348452349875,"score_gpt":0.256179107832765,"score_spread":0.2481137593804151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3167239440","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":[0.7215713,0.0054751355,0.24252948,0.0003803456,0.0001455955,0.00028994968,0.0033587185,0.0021968966,0.024052631],"genre_scores_gemma":[0.80732906,0.004021362,0.16883843,0.00025492787,0.00003181359,0.0003636885,0.0020779886,0.00014850155,0.01693423],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988728,0.00029624053,0.00006111672,0.00020425113,0.0005024369,0.000063108564],"domain_scores_gemma":[0.9995579,0.00010923792,0.00007080149,0.00003840954,0.00021259954,0.0000111024365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010592241,0.000396772,0.000409092,0.0010795615,0.0003542767,0.00037509212,0.00055258896,0.00074577663,0.0036023192],"category_scores_gemma":[0.00074037927,0.00021614924,0.00051249354,0.0011578106,0.00020458453,0.00040205495,0.00029676664,0.00047887687,0.0011293569],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022056069,0.000054527096,0.008942455,0.00041901515,0.000038619946,0.00011354379,0.00022530781,0.0009024315,0.96272177,0.0004862344,0.0008883295,0.024987131],"study_design_scores_gemma":[0.000026412094,0.0006361492,0.033945262,0.00009436272,0.00011812371,0.0007573979,0.0003430521,0.00987132,0.93579125,0.00034921983,0.01802344,0.000043981614],"about_ca_topic_score_codex":0.0018524278,"about_ca_topic_score_gemma":0.0037036354,"teacher_disagreement_score":0.0036023192,"about_ca_system_score_codex":0.00045111857,"about_ca_system_score_gemma":0.0004825746,"threshold_uncertainty_score":0.012050986},"labels":[],"label_agreement":null},{"id":"W4411000227","doi":"10.46488/nept.2025.v24i02.b4252","title":"A Complete Review on Ericoid Mycorrhiza: An Understudied Fungus in the Ericaceae Family","year":2025,"lang":"en","type":"review","venue":"Nature Environment and Pollution Technology","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"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":"Ericaceae; Mycorrhiza; Biology; Fungus; Botany; Ecology; Symbiosis; Paleontology","score_opus":0.020868241926350742,"score_gpt":0.2654538821900362,"score_spread":0.24458564026368546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411000227","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022156107,0.99824,0.00009580451,0.00017071821,0.00015856756,0.000006004589,0.00007727362,0.0000092488945,0.0010208717],"genre_scores_gemma":[0.00083217974,0.9981375,0.00020809198,0.00014309892,0.00009544806,0.0000057564575,0.00009179544,0.0000019464105,0.00048418745],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997354,0.00004045587,0.00006554879,0.000055120658,0.00008112813,0.000022290818],"domain_scores_gemma":[0.9992906,0.00035972634,0.00014462642,0.00001801381,0.00013974322,0.00004726476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004349449,0.00079021073,0.0011815306,0.0039739925,0.00035371448,0.0011681436,0.0006946043,0.00074586086,0.007252086],"category_scores_gemma":[0.0012908649,0.0002691977,0.0008508101,0.0039795283,0.0002663349,0.0016283317,0.00053357024,0.00089540577,0.0016605359],"study_design_candidate":"not_applicable","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":[0.00010033923,0.000076426135,0.0005046615,0.13689898,0.00029556945,0.00038624063,0.0002918333,0.000392199,0.0037934738,0.0023595493,0.04681231,0.80808836],"study_design_scores_gemma":[0.00000768573,0.00008856255,0.0015832363,0.017184867,0.0004324605,0.0010501628,0.000105858715,0.000049392806,0.0004234411,0.0006728603,0.97838265,0.000018797757],"about_ca_topic_score_codex":0.0013926591,"about_ca_topic_score_gemma":0.002973186,"teacher_disagreement_score":0.007252086,"about_ca_system_score_codex":0.00044362573,"about_ca_system_score_gemma":0.0020561717,"threshold_uncertainty_score":0.0242607},"labels":[],"label_agreement":null},{"id":"W4416277787","doi":"10.46488/nept.2025.v24i04.b4312","title":"An Analytical Investigation of Urban Expansion Patterns in the Kolkata Metropolitan Development Authority (KMDA) Region Using Geoinformatics","year":2025,"lang":"en","type":"article","venue":"Nature Environment and Pollution Technology","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":0,"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":"Geoinformatics; Metropolitan area; Urbanization; Urban expansion; Urban planning; Urban sprawl; Common spatial pattern; Land use","score_opus":0.011136000006072786,"score_gpt":0.24366357971265581,"score_spread":0.23252757970658303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416277787","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":[0.9892609,0.00016844382,0.0011374827,0.00006251685,0.0000026633245,0.0000505599,0.0039065303,0.000028303708,0.005382494],"genre_scores_gemma":[0.9925322,0.00025652171,0.0028797456,0.00001852066,0.000002684274,0.00006843701,0.0028884949,0.000007042742,0.0013462933],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999785,0.00004869886,0.000024134508,0.000041502237,0.000054009546,0.000046779896],"domain_scores_gemma":[0.9995573,0.0001308984,0.0001245075,0.00002888217,0.00012445277,0.00003392419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028978792,0.00016309557,0.00013346734,0.0043479437,0.0002896451,0.0007780879,0.00020798124,0.000104400024,0.0014605757],"category_scores_gemma":[0.00077570026,0.00013260347,0.00018143315,0.007588261,0.00029965033,0.00036992945,0.0006378551,0.00014281645,0.00028439672],"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":[0.000036293884,0.000023649045,0.95813006,0.0001079661,0.000044289343,0.00035160035,0.0021011992,0.0036520092,0.001370384,0.00111173,0.0011233516,0.0319476],"study_design_scores_gemma":[0.0000012937952,0.000016210992,0.98896575,0.000030910953,0.000014121622,0.00014028569,0.0044387695,0.0030492803,0.00038218286,0.00011447447,0.0028362807,0.000010327284],"about_ca_topic_score_codex":0.11299824,"about_ca_topic_score_gemma":0.25834826,"teacher_disagreement_score":0.11299824,"about_ca_system_score_codex":0.0019212499,"about_ca_system_score_gemma":0.0015184545,"threshold_uncertainty_score":0.22468102},"labels":[],"label_agreement":null},{"id":"W4416609968","doi":"10.46488/nept.2025.v24i04.d1774","title":"Modelling the Future: Groundwater Responses to Climate Change in Talomo-Lipadas Watershed, Davao City, Philippines","year":2025,"lang":"en","type":"article","venue":"Nature Environment and Pollution Technology","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"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":"Commission on Higher Education; International Development Research Centre","keywords":"Groundwater recharge; Baseflow; Climate change; Groundwater; Water scarcity; Downscaling; Hydrology (agriculture); MODFLOW; Water resources","score_opus":0.009020428603847535,"score_gpt":0.23370564743868713,"score_spread":0.2246852188348396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416609968","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":[0.9864966,0.0005994218,0.002901228,0.0022865718,0.000030467054,0.000039485774,0.0032067422,0.00018000463,0.0042594965],"genre_scores_gemma":[0.9960985,0.0005348921,0.0017023293,0.000066314155,0.0000121050925,0.000036045065,0.00093792914,0.00001952483,0.0005922795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99980897,0.00008310306,0.000010865699,0.000037342314,0.000024400748,0.000035324152],"domain_scores_gemma":[0.9996611,0.00010457949,0.00005655716,0.000020696974,0.000101817364,0.000055217468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052197947,0.0004103043,0.000247569,0.00067233935,0.00047819948,0.0013533385,0.00073684443,0.0005928379,0.0017861811],"category_scores_gemma":[0.0010062068,0.00017838473,0.0004485757,0.0017688577,0.000390827,0.0013034361,0.0007213586,0.00057443895,0.00013931822],"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":[0.0002217143,0.0002189938,0.35934237,0.0004822619,0.00024339874,0.0020306155,0.0023931153,0.5808728,0.0039907377,0.004150748,0.00597376,0.04007947],"study_design_scores_gemma":[0.00006194708,0.00021693097,0.17445298,0.00013473636,0.00017253598,0.00021838068,0.009124225,0.79055524,0.0021171288,0.004968894,0.017824488,0.00015248932],"about_ca_topic_score_codex":0.1442484,"about_ca_topic_score_gemma":0.17924829,"teacher_disagreement_score":0.1442484,"about_ca_system_score_codex":0.0029825242,"about_ca_system_score_gemma":0.002181207,"threshold_uncertainty_score":0.28681755},"labels":[],"label_agreement":null}]}