{"id":"W4408240085","doi":"10.5376/me.2024.15.0025","title":"Precision Pest Management: IoT and Remote Sensing in Tea Plant Protection","year":2024,"lang":"en","type":"article","venue":"Molecular Entomology","topic":"Food Supply Chain Traceability","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Integrated pest management; PEST analysis; Internet of Things; Remote sensing; Agroforestry; Environmental science; Business; Geography; Computer science; Agronomy; Biology; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003027608,0.00009820631,0.00010528,0.00003820009,0.00004117132,0.00004489611,0.00006765501,0.0001011314,0.00003279646],"category_scores_gemma":[0.00002663236,0.00004447302,0.0000332693,0.0002790947,0.00004410934,0.00002672191,0.00008241516,0.0001453921,0.00001625663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003844343,"about_ca_system_score_gemma":0.00000227766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005258026,"about_ca_topic_score_gemma":0.0006248208,"domain_scores_codex":[0.9990151,0.0001514397,0.0001430902,0.0003814572,0.0001079462,0.0002009988],"domain_scores_gemma":[0.9998268,0.00005467028,0.00001615483,0.00005382019,0.000009879378,0.00003868213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003751861,0.00002241433,0.0001499688,0.00004613262,0.00001280586,0.0006890252,0.0001193971,0.00001348097,0.2346004,0.000357346,0.00002292962,0.7639285],"study_design_scores_gemma":[0.002045884,0.004270443,0.3447895,0.001487533,0.0001908828,0.004487908,0.001805816,0.1654762,0.1963877,0.1713521,0.1049747,0.002731442],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959096,0.0003932264,0.0006731694,0.001935886,0.000141339,0.0003785653,0.000006115124,0.00008065128,0.0004814473],"genre_scores_gemma":[0.9990047,0.00002071852,0.0007662114,0.00007216451,0.00002807212,0.000002610489,0.00001692261,0.000001226441,0.0000873442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7611971,"threshold_uncertainty_score":0.1813557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01256865078419563,"score_gpt":0.2235583641520072,"score_spread":0.2109897133678116,"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."}}