{"id":"W2991474002","doi":"","title":"Towards the implementation of L-band Soil Moisture Brightness Temperatures in the Canadian Land Data Assimilation System (CaLDAS)","year":2016,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Data assimilation; Environmental science; Brightness; Moisture; Remote sensing; Assimilation (phonology); Water content; Atmospheric sciences; Meteorology; Geology; Geography; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007430582,0.00016785,0.0001586021,0.00004273446,0.000248245,0.0001416497,0.0006669734,0.0001087334,0.00004266744],"category_scores_gemma":[0.00003099446,0.00007488336,0.00003223071,0.0001872607,0.0001229211,0.0003170458,0.00007332219,0.0001629689,0.00002398385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001925738,"about_ca_system_score_gemma":0.0002146661,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.461212,"about_ca_topic_score_gemma":0.9520826,"domain_scores_codex":[0.998383,0.0001653992,0.00033393,0.0003352864,0.0004621289,0.0003201834],"domain_scores_gemma":[0.9990432,0.00007810006,0.0001692392,0.0005907693,0.00003514209,0.00008357241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000611148,0.0001051513,0.6087587,0.00007521047,0.00009917607,0.0001705441,0.006246234,0.002395753,0.1861076,0.001873306,0.01770916,0.176398],"study_design_scores_gemma":[0.000299084,0.00001883656,0.983821,0.00004909034,0.00001875452,0.00002494684,0.0005868452,0.0001635186,0.01315487,0.0001213457,0.001607932,0.0001338153],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776618,0.00002909713,0.00003627955,0.005699339,0.000221793,0.00028334,0.00003691131,0.0000132061,0.01601826],"genre_scores_gemma":[0.9992624,0.00001332212,0.0000724274,0.0002970496,0.0001711514,0.000003268049,0.00007248724,0.000009615192,0.00009829292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4908706,"threshold_uncertainty_score":0.5423758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03300188076814629,"score_gpt":0.2747738055745171,"score_spread":0.2417719248063708,"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."}}