{"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":"edceb9847ff4","filters":{"venue":"EUSAR 2014; 10th European Conference on Synthetic Aperture Radar; Proceedings of"}},"results":[{"id":"W371451046","doi":"","title":"Soil moisture retrieval using L-band time-series SAR data from the SMAPVEX12 experiment","year":2014,"lang":"en","type":"article","venue":"EUSAR 2014; 10th European Conference on Synthetic Aperture Radar; Proceedings of","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Synthetic aperture radar; Remote sensing; Water content; Environmental science; Radar; Vegetation (pathology); Inversion (geology); Moisture; Soil science; Meteorology; Geology; Geography; Computer science","authors":[{"name":"Seung Bum Kim","is_ca":false},{"name":"Huan Huang","is_ca":false},{"name":"Leung Tsang","is_ca":false},{"name":"Thomas J. Jackson","is_ca":false},{"name":"Heather McNairn","is_ca":true},{"name":"Jakob van Zyl","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02893530953440176,"gpt":0.2349377518090051,"spread":0.2060024422746033,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007915765,0.0006848632,0.0005196591,0.0004587734,0.0003096203,0.0006081957,0.0005816593,0.0005888921,0.0006893786],"category_scores_gemma":[0.0008936253,0.0002841165,0.0003285805,0.0007749722,0.0002596603,0.0005817068,0.0003531425,0.0005015647,0.000268348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008184396,"about_ca_system_score_gemma":0.0005649051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0472521,"about_ca_topic_score_gemma":0.05986302,"domain_scores_codex":[0.9997203,0.00006367371,0.0000139399,0.00007509397,0.0000826088,0.00004441196],"domain_scores_gemma":[0.9995613,0.00007933101,0.00003756882,0.0001223048,0.000162139,0.00003735436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.008154384,0.00226098,0.1173979,0.0003423975,0.0005058623,0.001037969,0.0005557665,0.3159407,0.4283765,0.001304196,0.0113149,0.1128084],"study_design_scores_gemma":[0.001044897,0.0009911864,0.4008607,0.00002308444,0.0001026865,0.000249184,0.0001820957,0.4707992,0.1177366,0.000435048,0.007454618,0.0001206913],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912236,0.00003441727,0.003266807,0.00004330978,0.00001453812,0.00006277819,0.003611959,0.0004033299,0.001339398],"genre_scores_gemma":[0.9750268,0.00003675494,0.01323408,0.00003819217,0.00001027149,0.00007878209,0.01046902,0.00009504059,0.001011144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0472521,"threshold_uncertainty_score":0.09395415,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2197439631","doi":"","title":"Biomass Estimation of Boreal Forests Using Single-Pass Polarimetric SAR Tomography at L-band","year":2014,"lang":"en","type":"article","venue":"EUSAR 2014; 10th European Conference on Synthetic Aperture Radar; Proceedings of","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Taiga; Remote sensing; Biomass (ecology); Polarimetry; Lidar; Environmental science; Boreal; L band; Tomography; Synthetic aperture radar; Forestry; Geology; Geography","authors":[{"name":"Yué Huang","is_ca":false},{"name":"Qiaoping Zhang","is_ca":false},{"name":"Marcus Schwaebisch","is_ca":false},{"name":"Ming Wei","is_ca":false},{"name":"Bryan Mercer","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01541196477915513,"gpt":0.2203213103420598,"spread":0.2049093455629047,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001493762,0.0003617685,0.0001309832,0.0006949542,0.0001585512,0.0003032962,0.0002418772,0.0001768675,0.0003783799],"category_scores_gemma":[0.0002554099,0.0001338949,0.0001197786,0.0003932629,0.0001583963,0.000425475,0.0001710247,0.0000977524,0.0001496489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001869169,"about_ca_system_score_gemma":0.0001750675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008154906,"about_ca_topic_score_gemma":0.02491369,"domain_scores_codex":[0.9999472,0.000007767905,0.000002296696,0.00001432844,0.00002183205,0.000006644564],"domain_scores_gemma":[0.9999119,0.000018922,0.00002399468,0.00000820657,0.00002854364,0.000008553884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002862936,0.0001526767,0.287342,0.0001590897,0.00007793771,0.0003136068,0.0002372783,0.06712059,0.382722,0.0004142987,0.0006151447,0.2605591],"study_design_scores_gemma":[0.00002660278,0.0002019952,0.5674378,0.00002261377,0.00007294471,0.0005638492,0.0003937191,0.3635314,0.06602675,0.00058208,0.001078749,0.00006148902],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9376896,0.000249524,0.05958615,0.00003531589,0.000005635447,0.00001930919,0.0003544861,0.0002268703,0.001833102],"genre_scores_gemma":[0.9647379,0.0001410552,0.03447854,0.00001015595,0.00000480294,0.000008049196,0.000274812,0.00001530153,0.0003293883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008154906,"threshold_uncertainty_score":0.01621485,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}