{"id":"W4408012062","doi":"10.1016/j.geomat.2025.100053","title":"Prediction and monitoring of soil pH using field reflectance spectroscopy and time-series Sentinel-2 remote sensing imagery","year":2025,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Remote sensing; Reflectivity; Environmental science; Series (stratigraphy); Field (mathematics); Time series; Soil science; Geology; Computer science; Optics; Mathematics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006769287,0.0007310908,0.0003484187,0.0006620207,0.0001516576,0.0003432957,0.0004328161,0.0004883021,0.0003173348],"category_scores_gemma":[0.0007478775,0.0002839002,0.0006753635,0.000610336,0.0001229546,0.0007173103,0.0002367702,0.000350531,0.0001241045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004506542,"about_ca_system_score_gemma":0.0005009047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01385959,"about_ca_topic_score_gemma":0.01401998,"domain_scores_codex":[0.9997856,0.00003923035,0.00001528027,0.00007510081,0.00006110813,0.00002366672],"domain_scores_gemma":[0.9997339,0.000064804,0.00005806234,0.00002240156,0.0001024839,0.00001836572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004616906,0.0008204961,0.2451594,0.0002308837,0.0002425539,0.0004235592,0.0001712952,0.5508716,0.09051296,0.0005914164,0.002114041,0.1084001],"study_design_scores_gemma":[0.00002242402,0.00008535834,0.03582938,0.000003796797,0.00002648584,0.0000265466,0.0000356995,0.9586286,0.005023299,0.0001188415,0.0001841322,0.00001549816],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609963,0.0001096668,0.03663533,0.00007735854,0.00002445249,0.00005799072,0.0006757804,0.0004717158,0.0009515437],"genre_scores_gemma":[0.9734796,0.0001308954,0.02490801,0.0000238391,0.000008437511,0.00004502308,0.0009016316,0.0000167326,0.0004857812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01385959,"threshold_uncertainty_score":0.02755785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01020675380705729,"score_gpt":0.2471420479575084,"score_spread":0.2369352941504511,"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."}}