{"id":"W2025977935","doi":"10.4141/p06-031","title":"Water management strategies to enhance fruit solids and yield of drip irrigated processing tomato","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Plant Science","topic":"Irrigation Practices and Water Management","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Preharvest; Drip irrigation; Irrigation; Agronomy; Yield (engineering); Lycopersicon; Water use; Deficit irrigation; Water-use efficiency; Evapotranspiration; Irrigation management; Environmental science; Mathematics; Horticulture; Postharvest; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0001470249,0.0002131246,0.0003672841,0.000153529,0.0002355898,0.0003259752,0.0003535252,0.0001628288,0.0004085355],"category_scores_gemma":[0.0002201306,0.0001399057,0.0001447087,0.0002224972,0.0002323585,0.0002933398,0.0001922464,0.0003060382,0.00004799158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002577208,"about_ca_system_score_gemma":0.0008937739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07579256,"about_ca_topic_score_gemma":0.219593,"domain_scores_codex":[0.9998851,0.00001482148,0.000009628255,0.00003546237,0.00003317972,0.00002183748],"domain_scores_gemma":[0.9997918,0.00002323972,0.00007819417,0.00001057532,0.00004122764,0.0000549732],"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":[0.0004321892,0.0001033492,0.01004598,0.00005342095,0.00001866683,0.00005933179,0.0001431714,0.0003089205,0.9855555,0.00001945221,0.00003720931,0.0032227],"study_design_scores_gemma":[0.00009867803,0.005230881,0.7533487,0.00001178159,0.0001005659,0.0001194145,0.0006488439,0.00302096,0.2345331,0.00006063309,0.002789201,0.00003729253],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997192,0.00004991347,0.00007222232,0.000007827134,7.316018e-7,0.00001038185,0.00004098122,0.00000515802,0.00009356947],"genre_scores_gemma":[0.9981688,0.0001234597,0.0006590989,0.00002561075,0.000001265251,0.00001863533,0.0002752701,0.000006447135,0.0007213016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07579256,"threshold_uncertainty_score":0.1507028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01768487781946302,"score_gpt":0.2410396720864607,"score_spread":0.2233547942669977,"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."}}