{"id":"W109013405","doi":"10.1006/jaer.2000.0630","title":"PA—Precision Agriculture","year":2001,"lang":"en","type":"article","venue":"Journal of Agricultural Engineering Research","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":689,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Precision agriculture; Weed; Remote sensing; Computer science; Field (mathematics); Scale (ratio); Agriculture; Agricultural engineering; Geography; Cartography; Engineering; Agronomy; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001991903,0.001260654,0.0005346725,0.001072281,0.001695476,0.001582205,0.0007254771,0.001224351,0.4518325],"category_scores_gemma":[0.0007592895,0.0003963046,0.000229561,0.001048246,0.0004419627,0.00156799,0.001099418,0.001729276,0.4138772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006513362,"about_ca_system_score_gemma":0.0007175673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002500372,"about_ca_topic_score_gemma":0.005488639,"domain_scores_codex":[0.9996639,0.00002211978,0.00001036091,0.0001502288,0.0001067937,0.00004661436],"domain_scores_gemma":[0.9995458,0.00006193158,0.00003854775,0.00009567355,0.0001875614,0.00007045731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001395181,0.0001277414,0.0008831751,0.000201832,0.00001052121,0.0001736958,0.00006252191,0.0003241663,0.005045525,0.01295982,0.5139549,0.4661167],"study_design_scores_gemma":[0.00001078292,0.00004685591,0.001061953,0.00002372589,0.000003260488,0.0002243698,0.00001856301,0.0002052828,0.0009102563,0.0009496507,0.9965414,0.000003964502],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00357418,0.002842125,0.005788543,0.002257294,0.0008609302,0.0001025668,0.002602652,0.002553673,0.979418],"genre_scores_gemma":[0.01232247,0.002093158,0.005079634,0.0006035105,0.0002784534,0.00008086742,0.00269081,0.000303364,0.9765477],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4518325,"threshold_uncertainty_score":0.7818944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0176057944710286,"score_gpt":0.2677633606700754,"score_spread":0.2501575661990468,"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."}}