{"id":"W4393853447","doi":"10.3390/horticulturae10040356","title":"Vegetable Response to Added Nitrogen and Phosphorus Using Machine Learning Decryption and the N/P Ratio","year":2024,"lang":"en","type":"article","venue":"Horticulturae","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Lactuca; Apium graveolens; Soil water; Solanum tuberosum; Human fertilization; Agronomy; Crop; Nitrogen; Chemistry; Mathematics; Horticulture; Environmental science; Biology; Soil 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":[0.0003226316,0.00009179398,0.00008385615,0.00001577056,0.0002111431,0.0001604108,0.0000482625,0.00003005879,0.00003405571],"category_scores_gemma":[0.00006085027,0.0000517948,0.00002196393,0.0001643736,0.0001072476,0.000152289,0.0001233589,0.0000976505,0.0000567807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005590261,"about_ca_system_score_gemma":0.000003635244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003847426,"about_ca_topic_score_gemma":0.00002295562,"domain_scores_codex":[0.9993194,0.00008801691,0.0001091826,0.0002044687,0.0001275015,0.0001514023],"domain_scores_gemma":[0.9997601,0.00007266778,0.00001671038,0.00007257046,0.000004543986,0.00007343032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002606051,0.0000547579,0.7943758,0.00004158448,0.00009980047,0.00007127223,0.02144312,0.0104305,0.1479887,0.000756554,0.0004322272,0.02169962],"study_design_scores_gemma":[0.001916842,0.0002308586,0.1540935,0.0001181526,0.000224142,0.0002630515,0.001055691,0.7758123,0.01371106,0.00615455,0.04579488,0.0006249752],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975516,0.001275691,0.0002552985,0.0005035148,0.00006759448,0.000183161,0.000002250807,0.00004798087,0.0001128956],"genre_scores_gemma":[0.9988261,0.0001235593,0.0005200345,0.0001214542,0.00002077464,0.00001336859,0.000004422868,0.000008464645,0.0003617565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7653818,"threshold_uncertainty_score":0.2112131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007120433952953089,"score_gpt":0.2121633192451109,"score_spread":0.2050428852921578,"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."}}