{"id":"W2025546572","doi":"10.5194/ars-3-211-2005","title":"Microwave sensors for detection of wild animals during pasture mowing","year":2005,"lang":"en","type":"article","venue":"Advances in radio science","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Pasture; Noon; Environmental science; Specular reflection; Microwave; Detector; Radar; Morning; Grazing; Remote sensing; Agronomy; Optics; Atmospheric sciences; Physics; Geography; Biology; Computer science; Telecommunications","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":[0.0001787504,0.0002008758,0.0001830715,0.0002908439,0.00007260916,0.0001270092,0.0002619819,0.0002573738,0.0009411232],"category_scores_gemma":[0.0002261504,0.0001036961,0.00009219931,0.0002194172,0.0001083019,0.0001880223,0.0001295048,0.0001622952,0.000258898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009397369,"about_ca_system_score_gemma":0.00005105992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001626056,"about_ca_topic_score_gemma":0.0004274006,"domain_scores_codex":[0.9998798,0.00002782811,0.00000407117,0.00003049204,0.00004889708,0.000008960124],"domain_scores_gemma":[0.9998287,0.00006711027,0.00004174437,0.00001271445,0.0000381194,0.00001162365],"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":[0.0001627222,0.00004056827,0.006660275,0.0001123463,0.00001999297,0.00007225217,0.00004917993,0.000712529,0.9517699,0.0001195391,0.0002439009,0.04003682],"study_design_scores_gemma":[0.00002878481,0.00137277,0.0756145,0.00003377951,0.0000847402,0.001002707,0.0001414741,0.02506789,0.8883587,0.0001811683,0.008080197,0.00003322936],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9056333,0.002104792,0.08922279,0.0000548777,0.00005746013,0.00003937286,0.0002251447,0.000443667,0.002218587],"genre_scores_gemma":[0.955862,0.0005678126,0.04003256,0.00004255545,0.00001609345,0.00002867211,0.0001659923,0.00001249086,0.003271783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009411232,"threshold_uncertainty_score":0.003148377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008679929130177337,"score_gpt":0.2396587984842736,"score_spread":0.2309788693540962,"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."}}