{"id":"W2559984691","doi":"10.2136/vzj2014.07.0081","title":"Laboratory Calibration Procedures of the Hydra Probe Soil Moisture Sensor:Infiltration Wet-Up vs. Dry-Down","year":2014,"lang":"en","type":"article","venue":"Vadose Zone Journal","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Environment Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency","keywords":"Infiltration (HVAC); Water content; Calibration; Mean squared error; Moisture; Environmental science; Soil science; Soil water; Remote sensing; Mathematics; Geology; Materials science; Geotechnical engineering; Statistics; Composite material","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000430277,0.0001646253,0.0001746915,0.00003946852,0.0003517327,0.00008293434,0.0002017222,0.0001339965,0.00007583554],"category_scores_gemma":[0.0001647258,0.000102656,0.0000977391,0.0003052985,0.0001734683,0.0003126127,0.00006409223,0.0004025655,0.00002879582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008940817,"about_ca_system_score_gemma":0.00007645888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002200416,"about_ca_topic_score_gemma":0.001905905,"domain_scores_codex":[0.9984653,0.0002113668,0.0003520169,0.0001960533,0.0005435757,0.0002316722],"domain_scores_gemma":[0.9992038,0.00003731435,0.0003578887,0.0002521182,0.00004369787,0.0001051993],"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":[0.0001734259,0.0002807954,0.2751019,0.0000958157,0.00008235765,0.00001424704,0.005494636,0.02244343,0.6272715,0.0002134993,0.03072421,0.03810425],"study_design_scores_gemma":[0.001035745,0.0002082824,0.8608595,0.0001917654,0.00009484802,0.0002268345,0.0004178211,0.01144999,0.1082933,0.001066276,0.01575662,0.000398966],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98369,0.00008140791,0.005123371,0.002669628,0.0009096416,0.0002446361,0.000001984077,0.00003926583,0.00724012],"genre_scores_gemma":[0.9967228,0.00002880333,0.001232461,0.0006719183,0.0004646711,6.503028e-7,0.000002199005,0.00001986047,0.000856594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5857577,"threshold_uncertainty_score":0.418619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004554608255247884,"score_gpt":0.1933037142763759,"score_spread":0.188749106021128,"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."}}