{"id":"W4242212743","doi":"10.4095/220052","title":"A Soil Moisture Monitoring Sensorweb Demonstration in the Context of Integrated Earth Sensing","year":2003,"lang":"en","type":"report","venue":"","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Context (archaeology); Earth (classical element); Environmental science; Moisture; Earth observation; Water content; Earth system science; Remote sensing; Soil science; Earth science; Geology; Engineering; Geotechnical engineering; Meteorology; Geography; Aerospace engineering; Satellite; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002880712,0.0001769343,0.0001880312,0.00008551245,0.0001625739,0.0002294686,0.0004151569,0.0003004989,0.001533413],"category_scores_gemma":[0.0004572974,0.0001151708,0.00009129068,0.0002210938,0.0002422241,0.0005664472,0.0004214931,0.000435843,0.0002404784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001812061,"about_ca_system_score_gemma":0.0002872219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004478888,"about_ca_topic_score_gemma":0.00927092,"domain_scores_codex":[0.9998678,0.00002816426,0.000004526067,0.00002117862,0.00005726664,0.00002107763],"domain_scores_gemma":[0.9996753,0.00009032035,0.00001760452,0.00005683648,0.00009317268,0.00006671527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00177068,0.001023407,0.02890685,0.0003638489,0.00008909334,0.002641577,0.001318263,0.04442209,0.7689563,0.004189467,0.01178353,0.1345349],"study_design_scores_gemma":[0.0005080685,0.003171112,0.07313568,0.00005510266,0.00006368898,0.001327934,0.001140529,0.2772276,0.5988987,0.002391906,0.0420057,0.00007404642],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9538175,0.00004761831,0.0393821,0.0002429286,0.00003071363,0.0001043192,0.000428768,0.001709601,0.004236476],"genre_scores_gemma":[0.9695748,0.00006042704,0.02782875,0.00005489953,0.000006245658,0.00004285606,0.0004501061,0.00005486195,0.001927105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004478888,"threshold_uncertainty_score":0.008905649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03960253205168308,"score_gpt":0.3164560280939514,"score_spread":0.2768534960422683,"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."}}