{"id":"W3010087491","doi":"10.25165/ijabe.v13i1.3905","title":"Performance evaluation and calibration of capacitance sensor for estimating the salinity of reclaimed land","year":2020,"lang":"en","type":"article","venue":"International journal of agricultural and biological engineering","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Water content; Reflectometry; Soil science; Capacitance probe; Capacitance; Salinity; Soil salinity; Environmental science; Soil water; Gravimetric analysis; Bulk density; Materials science; Remote sensing; Time domain; Geotechnical engineering; Chemistry; 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":[0.000164737,0.00004055546,0.00007855059,0.000005744178,0.00001801416,0.000006689276,0.00005046987,0.00002485843,0.000002485611],"category_scores_gemma":[0.0001712827,0.00001746231,0.00002442665,0.00003378413,0.00003676969,0.00007372138,0.00001610582,0.00005158345,4.77769e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001040283,"about_ca_system_score_gemma":0.000001857258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007623042,"about_ca_topic_score_gemma":0.000001771191,"domain_scores_codex":[0.9996059,0.00001281951,0.0001716348,0.00004560014,0.0001284311,0.00003560333],"domain_scores_gemma":[0.9996844,0.00009052301,0.0001338628,0.00001072054,0.00005879101,0.00002169901],"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":[0.0001071712,0.00001735609,0.06618452,0.00002580854,0.00007431403,7.122268e-7,0.0008205681,0.1577683,0.718457,0.00001996645,0.00003605627,0.05648829],"study_design_scores_gemma":[0.0002406785,0.0001491343,0.7492971,0.00004271568,0.00001598536,0.00004138231,0.00008244997,0.2344724,0.01558296,0.00002007504,0.00001512736,0.00004004518],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974273,0.00005983091,0.001497148,0.000828907,0.00009673768,0.00005760582,0.000001540998,0.000002100624,0.0000288104],"genre_scores_gemma":[0.9926116,0.00002973022,0.007196879,0.00003105271,0.0001269165,2.404767e-7,0.000001926993,8.455064e-7,8.427334e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.702874,"threshold_uncertainty_score":0.07120922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02545630642521731,"score_gpt":0.2293927285246186,"score_spread":0.2039364220994013,"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."}}