{"id":"W4396214946","doi":"10.1109/tgrs.2024.3394744","title":"Mapping Surface Water Fraction Over the Pan-Tropical Region Using CYGNSS Data","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Environmental science; Remote sensing; Surface water; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003192983,0.0002040955,0.0001473816,0.00007509278,0.001024939,0.0002850128,0.0002063547,0.0001199573,0.0000149509],"category_scores_gemma":[0.000006250698,0.0001187888,0.00006577381,0.0004768663,0.0005018027,0.0005983714,0.0000238591,0.0004619311,0.00006817957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001434033,"about_ca_system_score_gemma":0.00002121581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003625165,"about_ca_topic_score_gemma":0.0006266298,"domain_scores_codex":[0.9981196,0.0001000383,0.0002217847,0.0007254825,0.0004095744,0.000423498],"domain_scores_gemma":[0.9991793,0.000117788,0.00003344359,0.0005715012,0.000009922034,0.00008804685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001243283,0.00001419124,0.0000247344,0.00001516048,0.00001667952,0.00008764308,0.0009777963,0.002642934,0.07437846,9.137983e-7,0.000112485,0.9217166],"study_design_scores_gemma":[0.00009848399,0.00002708709,0.004511415,0.0001872545,0.00004907064,0.0006910087,0.000479178,0.9772726,0.009471718,0.0001892388,0.006769642,0.0002532698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4615337,0.00004730085,0.5361822,0.000754127,0.0009271738,0.0001040354,0.000001109053,0.00007245371,0.0003778409],"genre_scores_gemma":[0.9869556,0.0001417614,0.0119346,0.0004019289,0.0001305448,1.286572e-8,0.000001619745,0.00002197601,0.0004118995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9746297,"threshold_uncertainty_score":0.7883103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03376469114336635,"score_gpt":0.262768334392137,"score_spread":0.2290036432487707,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}