{"id":"W2547387523","doi":"10.1109/igarss.2016.7729908","title":"Biophysiological spectral indices retrieval and statistical analysis for red palm weevil stressattack prediction using Worldview-3 data","year":2016,"lang":"en","type":"article","venue":"","topic":"Date Palm Research Studies","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"Arabian Gulf University","keywords":"Weevil; Normalized Difference Vegetation Index; Artificial intelligence; Palm; Vegetation (pathology); Preprocessor; Statistical analysis; Computer science; Remote sensing; Search engine indexing; Pattern recognition (psychology); Mathematics; Statistics; Environmental science; Botany; Biology; Geology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004691795,0.0001429528,0.0002966993,0.00003173371,0.0002563393,0.00008175361,0.0003399641,0.00006980628,0.0006778018],"category_scores_gemma":[0.0005704372,0.0000381813,0.00005870075,0.0005324529,0.0002589168,0.0002270338,0.0004210027,0.00006539494,0.000005813524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002485011,"about_ca_system_score_gemma":0.000007275446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009706939,"about_ca_topic_score_gemma":0.0003894521,"domain_scores_codex":[0.9983668,0.0001178367,0.0002529271,0.0006009075,0.0002763256,0.000385152],"domain_scores_gemma":[0.9986038,0.0009781701,0.0000739331,0.0001322927,0.00007136116,0.000140413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008076227,0.0001853148,0.5764536,0.00003225635,0.0008105572,0.000008107628,0.00001584474,0.000003140056,0.349835,0.0005760884,0.004688742,0.06658372],"study_design_scores_gemma":[0.000215219,0.000304511,0.9936702,0.00001538794,0.0001631882,0.000001013143,0.0000838151,0.00164496,0.0006312876,0.0006994986,0.002434964,0.0001359941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920947,0.0001276613,0.0007130451,0.001623575,0.0000414504,0.0002998192,0.004900124,0.00006018518,0.0001394739],"genre_scores_gemma":[0.9968047,0.0004442582,0.001675465,0.00003079068,0.0002377535,0.000006132852,0.0006402493,7.905555e-7,0.0001598979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4172166,"threshold_uncertainty_score":0.7421455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1599648408469808,"score_gpt":0.3467094925050251,"score_spread":0.1867446516580443,"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."}}