{"id":"W4386136214","doi":"10.1007/s11119-023-10059-z","title":"Integration of ultrasonic and optical sensing systems to assess sugarcane biomass and N-uptake","year":2023,"lang":"en","type":"article","venue":"Precision Agriculture","topic":"Sugarcane Cultivation and Processing","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Financiadora de Estudos e Projetos; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Canopy; Biomass (ecology); Environmental science; Growing season; Remote sensing; Agronomy; Ultrasonic sensor; Crop; Sampling (signal processing); Spatial variability; Mathematics; Botany; Geography; Biology; Engineering; Statistics; Filter (signal processing)","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":[0.0003526743,0.0001293727,0.0001878094,0.00003071993,0.0001506934,0.0001415,0.00008170798,0.0001225804,0.00001884103],"category_scores_gemma":[0.0003181277,0.00004386107,0.00002975498,0.000821917,0.0000328687,0.0001165429,0.00005330544,0.00009439409,0.00001026152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001301241,"about_ca_system_score_gemma":0.000004620184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007178634,"about_ca_topic_score_gemma":0.0001121193,"domain_scores_codex":[0.9989781,0.00006732628,0.0002436176,0.0002855897,0.000250875,0.0001745025],"domain_scores_gemma":[0.9991589,0.0004144325,0.00007862221,0.00003662194,0.0001718704,0.000139533],"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":[0.00001512931,0.000009342818,0.001109481,0.00001621956,0.000005009721,0.000001628068,0.0002012901,0.00001086824,0.8709174,0.0001493172,0.0007534387,0.1268108],"study_design_scores_gemma":[0.0002476074,0.0002003572,0.9309994,0.0003414777,0.0000218025,0.00006968981,0.004206395,0.001425207,0.05069139,0.0001687104,0.01132763,0.0003003177],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977513,0.0001851247,0.0001761317,0.001134657,0.0001198174,0.0002316924,0.00002466761,0.00009016758,0.000286438],"genre_scores_gemma":[0.9989758,0.00006573386,0.0004763293,0.00006336331,0.0001020374,0.000005016259,0.00006336057,0.000001064592,0.0002473496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9298899,"threshold_uncertainty_score":0.1788602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05967035629013601,"score_gpt":0.2785341988053211,"score_spread":0.2188638425151851,"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."}}