{"id":"W4413204468","doi":"10.1109/ic2em63689.2025.11101278","title":"Meander-Line based Microwave Sensor for Soil Water Content Monitoring","year":2025,"lang":"en","type":"article","venue":"","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Meander (mathematics); Microwave; Environmental science; Remote sensing; Water content; Line (geometry); Computer science; Geology; Telecommunications; Geotechnical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001805623,0.0003637161,0.0002880089,0.0003129999,0.0001116148,0.0002228228,0.000501196,0.0005555403,0.0009132901],"category_scores_gemma":[0.0003590608,0.0002108181,0.0002618586,0.0002367203,0.0001630004,0.0006614588,0.0001862405,0.0002471124,0.0003546199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002352094,"about_ca_system_score_gemma":0.0001106207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002371536,"about_ca_topic_score_gemma":0.0007610208,"domain_scores_codex":[0.9997661,0.00005019483,0.00000622433,0.00005553185,0.0001060986,0.00001601668],"domain_scores_gemma":[0.999783,0.00007890392,0.0000388373,0.00002352646,0.00006755887,0.000008208454],"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":[0.0001064754,0.00004582583,0.00192845,0.0001163508,0.00002675157,0.000084429,0.000040052,0.002861645,0.9571469,0.0004444584,0.0005439008,0.03665484],"study_design_scores_gemma":[0.00001964479,0.0004298033,0.004626388,0.00001103779,0.00006069007,0.0006523621,0.0000483433,0.1063825,0.8809696,0.0003668728,0.006388755,0.00004409098],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3950616,0.001502906,0.5952705,0.0003270639,0.0001559176,0.00007283646,0.0003523722,0.002612276,0.004644527],"genre_scores_gemma":[0.8515269,0.0003753015,0.1458284,0.000141169,0.00002880605,0.00003404257,0.0001019572,0.0000415227,0.001922001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009132901,"threshold_uncertainty_score":0.003055274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03338394738454013,"score_gpt":0.2492643574925655,"score_spread":0.2158804101080254,"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."}}