{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":2,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":2,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"8057805a9147","filters":{"venue":"Journal of spatial hydrology"}},"results":[{"id":"W2254426554","doi":"","title":"Estimating land-use change impacts on direct runoff and non-point source pollutant loads in the Richland Creek basin (Illinois, USA) by applying the L-THIA model","year":2007,"lang":"en","type":"article","venue":"Journal of spatial hydrology","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Manitoba","funders":"","keywords":"Surface runoff; Environmental science; Nonpoint source pollution; Hydrology (agriculture); Land use; Pollutant; Land use, land-use change and forestry; Structural basin; Water quality; Agricultural land; Pollution; Environmental engineering; Engineering; Civil engineering; Ecology; Geology","authors":[{"name":"Woonsup Choi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02752031641363263,"gpt":0.2753888594596398,"spread":0.2478685430460071,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002847404,0.000146116,0.0002436522,0.00006087723,0.000216086,0.00007267296,0.0002443359,0.00009538935,0.00005396971],"category_scores_gemma":[0.00006195362,0.0000844976,0.00005844067,0.0001175273,0.0001699757,0.0002169438,0.00008057859,0.0004298129,0.00001093253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001026717,"about_ca_system_score_gemma":0.00001381928,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01129679,"about_ca_topic_score_gemma":0.005668974,"domain_scores_codex":[0.9984024,0.0002391983,0.0004642758,0.0001571054,0.0003774577,0.0003595531],"domain_scores_gemma":[0.9990145,0.0003493592,0.0003656299,0.0001546485,0.000007304869,0.0001085404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001238084,0.0007292808,0.6386635,0.00003466152,0.00009554732,0.0002407762,0.02776169,0.2298638,0.0125646,0.00002954222,0.002906711,0.08587188],"study_design_scores_gemma":[0.00195326,0.001173336,0.5363576,0.00008318435,0.00006714533,0.0004391753,0.0002438694,0.4538416,0.001004742,0.0006276628,0.003882417,0.0003259618],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9744442,0.00005367805,0.02113135,0.003617312,0.0001369983,0.0002827161,0.00001233537,0.000004324044,0.0003171047],"genre_scores_gemma":[0.9950169,0.00003379408,0.0008452297,0.003873029,0.0001836231,0.000008656278,0.000001347563,0.000009595996,0.00002778789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2239778,"threshold_uncertainty_score":0.9952871,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2146517375","doi":"","title":"Development of a Multivariate Regression Model for Soil Nitrate Nitrogen Content Prediction","year":2006,"lang":"en","type":"article","venue":"Journal of spatial hydrology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Multivariate statistics; Multivariate analysis of variance; Environmental science; Nonpoint source pollution; Bayesian multivariate linear regression; Multivariate analysis; Nitrate; Water content; Statistics; Regression analysis; Mathematics; Hydrology (agriculture); Pollution; Ecology; Engineering","authors":[{"name":"Xixi Wang","is_ca":false},{"name":"Assefa M. Melesse","is_ca":false},{"name":"Wanhong Yang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02827636754077446,"gpt":0.2443259689069635,"spread":0.2160496013661891,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003331274,0.00008382712,0.0001948962,0.00004677598,0.00007220633,0.000004567095,0.00009417698,0.00006753866,0.00002986552],"category_scores_gemma":[0.00003560836,0.0000647462,0.00006007662,0.00003381289,0.00005886371,0.00006626228,0.00004449066,0.00008063236,0.00000283841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007240371,"about_ca_system_score_gemma":0.00004287998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004676871,"about_ca_topic_score_gemma":0.0004592874,"domain_scores_codex":[0.9989914,0.00002270067,0.0005481918,0.00009916576,0.0001797915,0.0001587152],"domain_scores_gemma":[0.9992861,0.00003874686,0.0005234467,0.00005707734,0.00004699953,0.00004759484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009438391,0.0003820264,0.03077151,0.00003066252,0.00008388843,0.00001407013,0.001157417,0.3200328,0.6123896,0.0003614286,0.0007309966,0.03310176],"study_design_scores_gemma":[0.001805061,0.0002801097,0.02074848,0.00003584881,0.00004732126,0.00003096708,0.00002459412,0.9433773,0.02309196,0.009576995,0.0008828347,0.00009857738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6888108,0.00001702645,0.3107277,0.00006245921,0.0001261907,0.00008396317,0.000009274627,0.000003069042,0.0001594469],"genre_scores_gemma":[0.9549397,0.000005641334,0.04485961,0.0000384783,0.00007055327,0.000006122058,0.000007065013,0.000007281834,0.00006551964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6233445,"threshold_uncertainty_score":0.2640274,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}