{"id":"W6981011514","doi":"","title":"Development of a smart variable rate sprayer using deep convolutional neural networks for site-specific application of agrochemicals","year":2020,"lang":"en","type":"article","venue":"IslandScholar (University of Prince Edward Island)","topic":"Psychological Well-being and Life Satisfaction","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sprayer; Precision agriculture; Variable (mathematics); Agrochemical; Convolutional neural network; Field (mathematics); Identification (biology); Shadow (psychology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004337482,0.0001470861,0.0003630714,0.00007411517,0.0001377829,0.000007188935,0.0002554189,0.0002048917,0.0003245669],"category_scores_gemma":[0.00004062125,0.0001647737,0.0001189402,0.0002340471,0.00009206744,0.0001207065,0.00007527117,0.0002263348,0.00001476567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003939316,"about_ca_system_score_gemma":0.00003639294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006281477,"about_ca_topic_score_gemma":0.00004740384,"domain_scores_codex":[0.9987529,0.0001119392,0.0003386482,0.0003924132,0.0001716004,0.00023252],"domain_scores_gemma":[0.9989074,0.000165021,0.0004131092,0.0002242903,0.0001938518,0.00009634023],"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":[0.01385705,0.001539647,0.2292491,0.0007630857,0.001319562,0.00002019731,0.034578,0.03110762,0.631063,0.02041106,0.006361121,0.02973055],"study_design_scores_gemma":[0.02185504,0.001569834,0.360536,0.0003333104,0.0006542776,0.00004228657,0.007390793,0.3483657,0.008497143,0.002615372,0.2459107,0.002229581],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5213711,0.00008974979,0.4768276,0.0000690594,0.0001314147,0.000241515,0.00003722356,0.0000221894,0.001210088],"genre_scores_gemma":[0.9736747,0.00001220538,0.02599827,0.00005470805,0.00009270038,0.000002071868,0.00008273378,0.00001165656,0.00007094823],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6225658,"threshold_uncertainty_score":0.6719278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02695557930251916,"score_gpt":0.2560189148140524,"score_spread":0.2290633355115333,"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."}}