{"id":"W4310170198","doi":"10.1016/j.iot.2022.100649","title":"Knowledge graph and deep learning based pest detection and identification system for fruit quality","year":2022,"lang":"en","type":"article","venue":"Internet of Things","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Guangdong Academy of Agricultural Sciences; Department of Agriculture of Guangdong Province","keywords":"Identification (biology); PEST analysis; Computer science; Quality (philosophy); Artificial intelligence; Biology; Botany","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":[0.0004368681,0.00005947851,0.00009957546,0.00001205218,0.0001718335,0.00004060774,0.00008111016,0.00003056114,0.00001839517],"category_scores_gemma":[0.00003952242,0.00002561242,0.0000460935,0.00009639063,0.00002223726,0.00008396595,0.00005696929,0.00008086619,8.035117e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000182635,"about_ca_system_score_gemma":0.000001114234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004420398,"about_ca_topic_score_gemma":0.0002209173,"domain_scores_codex":[0.9994248,0.00008566408,0.0001639254,0.0001679265,0.00008204967,0.00007564633],"domain_scores_gemma":[0.9996145,0.0001615161,0.0001301163,0.00001870704,0.00004905598,0.00002609036],"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":[0.0001136268,0.0000824101,0.0156806,0.0001801737,0.00002673385,4.769042e-7,0.002432823,0.0000116706,0.8602602,0.0006493072,0.0001668127,0.1203952],"study_design_scores_gemma":[0.000878641,0.001689667,0.7509905,0.0001307622,0.0001074771,0.0000398952,0.01530112,0.01465626,0.1499643,0.0007707627,0.06488071,0.0005899754],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987482,0.0002831548,0.0003430911,0.000164372,0.0001475826,0.0001475124,0.00000496972,0.00004204947,0.0001190998],"genre_scores_gemma":[0.9995239,0.000002772124,0.00002527432,0.00003117643,0.00004778033,0.00004079516,0.00002321138,5.566253e-7,0.0003044723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7353098,"threshold_uncertainty_score":0.1321622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01979611279870575,"score_gpt":0.2386067846480265,"score_spread":0.2188106718493208,"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."}}