{"id":"W6995972095","doi":"","title":"Predicting crop water requirements and yield for tomato under a humid climate","year":2020,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Irrigation; Biomass (ecology); Semi-arid climate; Deficit irrigation; Yield (engineering); Crop yield; Arid; Water use","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001791027,0.00043751,0.0002328109,0.0001929784,0.0002227574,0.0003561431,0.0003875642,0.0002703642,0.000595701],"category_scores_gemma":[0.0004435556,0.0001963788,0.0002281101,0.0002930762,0.0001453644,0.000310067,0.0001398912,0.0001997701,0.0001283475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003126744,"about_ca_system_score_gemma":0.001661642,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5162438,"about_ca_topic_score_gemma":0.6212251,"domain_scores_codex":[0.9999368,0.00000621564,0.000002916709,0.0000248929,0.00001712469,0.00001200393],"domain_scores_gemma":[0.9998604,0.00004958899,0.00002352304,0.000006966526,0.00004539892,0.00001407328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001747023,0.0001261337,0.1364158,0.0001254839,0.00006423036,0.000194954,0.0001413995,0.8063619,0.03380771,0.0002019972,0.000721721,0.02166404],"study_design_scores_gemma":[0.00001997222,0.00008617262,0.1691318,0.000007347362,0.00002261904,0.0000354287,0.0001513566,0.824503,0.005286464,0.000141093,0.0005895219,0.00002529986],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965233,0.000046973,0.002034706,0.0000226895,9.308595e-7,0.00001688582,0.0005229945,0.00005922814,0.0007723458],"genre_scores_gemma":[0.9965562,0.00005389429,0.002247218,0.00000648789,6.653261e-7,0.00001331104,0.0006218806,0.00001090928,0.0004894746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5162438,"threshold_uncertainty_score":0.9732104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04281725639507434,"score_gpt":0.2554640803167424,"score_spread":0.2126468239216681,"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."}}