{"id":"W4388778210","doi":"10.1007/978-981-99-4863-5_1","title":"Agricultural Meteorology: A Preview","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Agroforestry and silvopastoral systems","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Agriculture; Scope (computer science); Cropping; Environmental science; Climate change; Agricultural productivity; Geography; Meteorology; Environmental resource management; Ecology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0005778045,0.001708559,0.0009245445,0.005458731,0.0006457806,0.003262704,0.0007661391,0.001029859,0.06134861],"category_scores_gemma":[0.0006770884,0.0005348221,0.0003720823,0.005857289,0.0006122838,0.002887379,0.001254303,0.001578902,0.04525667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001179929,"about_ca_system_score_gemma":0.001174335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004920066,"about_ca_topic_score_gemma":0.01366485,"domain_scores_codex":[0.9997649,0.00002757535,0.00001751992,0.00003808183,0.0001342317,0.00001775104],"domain_scores_gemma":[0.9996386,0.00008844581,0.00002252061,0.00003642778,0.0001603572,0.00005368215],"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":[0.00001995992,0.00004644253,0.0002023221,0.0005463582,0.000007078503,0.00006096121,0.0000937174,0.0005287273,0.0005480145,0.01048457,0.7006952,0.2867668],"study_design_scores_gemma":[0.000001505176,0.000006195616,0.0002990883,0.0001470274,0.000001527872,0.00004830153,0.00001916957,0.00005170166,0.0000396514,0.001604059,0.9977787,0.000002997102],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0007840606,0.4084477,0.009047266,0.005852679,0.03400848,0.0001213962,0.002580754,0.001042175,0.5381154],"genre_scores_gemma":[0.00404222,0.1698545,0.003542954,0.00226215,0.01832606,0.0000816536,0.002286369,0.0007497183,0.7988544],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06134861,"threshold_uncertainty_score":0.2052315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04756285714555747,"score_gpt":0.21659275821563,"score_spread":0.1690299010700726,"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."}}