{"id":"W2562568621","doi":"10.1038/srep39307","title":"Yields and Nutritional of Greenhouse Tomato in Response to Different Soil Aeration Volume at two depths of Subsurface drip irrigation","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Plant responses to water stress","field":"Agricultural and Biological Sciences","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Higher Education Discipline Innovation Project","keywords":"Aeration; Sugar; Irrigation; Greenhouse; Drip irrigation; Agronomy; Environmental science; Yield (engineering); Volume (thermodynamics); Chemistry; Horticulture; Animal science; Biology; Food science; Materials 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008527673,0.00009329589,0.0001645354,0.00005766676,0.00008769732,0.00004081673,0.00008811954,0.00005470596,0.0001019165],"category_scores_gemma":[0.0002052669,0.00003542769,0.00004060288,0.000263745,0.0001276141,0.0001352522,0.00008846082,0.00002694229,0.000005332589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004717378,"about_ca_system_score_gemma":0.00001559851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001964288,"about_ca_topic_score_gemma":0.01008586,"domain_scores_codex":[0.9984912,0.0001498283,0.0004235208,0.0003879104,0.0003771094,0.0001703929],"domain_scores_gemma":[0.9992713,0.0002155112,0.0001977903,0.0001211029,0.0001068321,0.00008740809],"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":[0.0003324843,0.00005430734,0.1302383,0.000006190172,0.00000228749,0.00002450831,0.00008856219,0.00001366823,0.8658813,0.000008544918,0.000402284,0.002947585],"study_design_scores_gemma":[0.0001083414,0.00007236396,0.5994273,0.00007969299,0.000002597043,0.00003740763,0.00001881809,0.00004267919,0.3990989,0.0004855566,0.0005567809,0.00006949896],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983879,0.00002784001,0.000008665578,0.0009323365,0.0003152566,0.0002259576,0.00004909648,0.00001759372,0.00003530471],"genre_scores_gemma":[0.9979508,0.000002223223,0.00005062885,0.000008365557,0.00001492367,0.00001268524,0.00003501376,7.756813e-7,0.001924564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.469189,"threshold_uncertainty_score":0.5628148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343244884570879,"score_gpt":0.2170402782427749,"score_spread":0.2036078293970661,"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."}}