{"id":"W4319441756","doi":"10.3390/rs15040896","title":"Study of Genetic Variation in Bermuda Grass along Longitudinal and Latitudinal Gradients Using Spectral Reflectance","year":2023,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Natural Science Foundation of China","keywords":"Canopy; Multispectral image; Remote sensing; Spectral signature; Hyperspectral imaging; Environmental science; Reflectivity; Spatial variability; Genetic variation; Biology; Ecology; Geography; Mathematics; Physics","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":[0.000397422,0.0001711293,0.0001299151,0.0006528386,0.0001878266,0.000168729,0.0001010444,0.0001225579,0.000432312],"category_scores_gemma":[0.0005115792,0.00008806688,0.0001590653,0.0005173787,0.0001701092,0.0001213898,0.0001317883,0.0001342662,0.00008122198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002358732,"about_ca_system_score_gemma":0.0001477142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006872999,"about_ca_topic_score_gemma":0.01536628,"domain_scores_codex":[0.9998447,0.00004256903,0.000008692661,0.00006225559,0.00002242897,0.00001933223],"domain_scores_gemma":[0.9997103,0.00007432971,0.0001011794,0.00002802816,0.00004585438,0.00004034251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000213214,0.00009437081,0.8335857,0.00003463887,0.0002112975,0.0001190043,0.000821176,0.001050095,0.1378015,0.0001903325,0.00007452783,0.02580413],"study_design_scores_gemma":[0.000001419376,0.00002685675,0.9985368,0.000002413489,0.00001090886,0.00003012694,0.00006866711,0.0008057294,0.0004030257,0.00001853569,0.0000925518,0.000002896286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993384,0.00004779966,0.0004466871,0.000004200047,9.856217e-7,0.000002077176,0.0000402004,0.000002842479,0.0001167438],"genre_scores_gemma":[0.9987872,0.00004043735,0.0008867728,0.00000461848,0.000001457803,0.000004040429,0.0001187661,0.000002855272,0.0001539534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006872999,"threshold_uncertainty_score":0.01366603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02903678910730796,"score_gpt":0.2709583569384988,"score_spread":0.2419215678311909,"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."}}