{"id":"W3109221266","doi":"10.3390/rs12203304","title":"Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network","year":2020,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China; China Scholarship Council; Agriculture and Agri-Food Canada; National Natural Science Foundation of China","keywords":"Remote sensing; Leaf area index; Environmental science; Thematic Mapper; Satellite; Mean squared error; Satellite imagery; Geography; Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005098495,0.0003960998,0.0006041725,0.0000182123,0.0002059133,0.00008861347,0.0004854661,0.0002791928,0.00008444452],"category_scores_gemma":[0.0003566474,0.0003542602,0.0001231588,0.0005005424,0.0001153184,0.0001405741,0.0004279211,0.0005679342,0.00004051163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002077655,"about_ca_system_score_gemma":0.00004332953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002033667,"about_ca_topic_score_gemma":0.0002239158,"domain_scores_codex":[0.9964671,0.0003848796,0.0006102644,0.0009958817,0.0009916836,0.0005501612],"domain_scores_gemma":[0.9976724,0.0004420661,0.0004565772,0.001120272,0.00005764555,0.0002510219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002301896,0.0001043414,0.0228461,0.00005121703,0.0001307779,0.0001489086,0.0005316776,0.1390649,0.673794,5.646673e-7,0.001906753,0.1611905],"study_design_scores_gemma":[0.0008403496,0.000111685,0.009802535,0.0003892516,0.00009780509,0.00000940595,0.0001170583,0.967894,0.01831946,0.000005798321,0.0020035,0.0004091162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.777267,0.00004913261,0.2180336,0.001113921,0.0004232626,0.0005661667,0.00002652917,0.0001511648,0.002369189],"genre_scores_gemma":[0.7647297,0.00001329397,0.2320666,0.002761213,0.0002662007,4.862694e-9,0.00007188749,0.00004542718,0.00004565874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8288291,"threshold_uncertainty_score":0.9998909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08002523896411515,"score_gpt":0.2870996517044724,"score_spread":0.2070744127403572,"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."}}