{"id":"W4404524569","doi":"10.3390/drones8110686","title":"Drones in Precision Agriculture: A Comprehensive Review of Applications, Technologies, and Challenges","year":2024,"lang":"en","type":"review","venue":"Drones","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Mitacs","keywords":"Drone; Agriculture; Precision agriculture; Computer science; Engineering; Engineering ethics; Biotechnology; Biology; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001580378,0.0003908522,0.001416908,0.00004404989,0.00004851489,0.00002600176,0.0003825494,0.0004065169,0.00001729692],"category_scores_gemma":[0.00003134476,0.0001090325,0.0002623915,0.0008512558,0.00008203701,0.00006183888,0.0002655475,0.0003081849,0.0000469307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000262672,"about_ca_system_score_gemma":0.00001198318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003604889,"about_ca_topic_score_gemma":0.0001504778,"domain_scores_codex":[0.9983065,0.00009848841,0.0006078737,0.0005722449,0.000202578,0.0002122887],"domain_scores_gemma":[0.9992326,0.0002704098,0.0002658602,0.0001200118,0.00007355212,0.00003750611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[5.89284e-7,0.00004156383,0.000001649003,0.06604842,0.00002729807,0.000003384306,0.000009087603,3.279619e-9,0.00002400187,0.0004046957,0.002751185,0.9306881],"study_design_scores_gemma":[0.00001957107,0.00005445225,0.00008726215,0.0753312,0.0002609709,0.00004169426,0.0001697623,5.403764e-8,0.000004392532,0.0004202144,0.9233632,0.0002472116],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001485747,0.9965271,1.488937e-7,0.001550663,0.00007526228,0.001424972,0.00008906981,0.0001330817,0.0001848918],"genre_scores_gemma":[0.00001165143,0.9987927,0.00002732515,0.00003091944,0.0001527783,0.0005883406,0.0002873379,0.000002320794,0.0001066435],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9304409,"threshold_uncertainty_score":0.4446217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06672733749496383,"score_gpt":0.2932334768265317,"score_spread":0.2265061393315679,"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."}}