{"id":"W3178400248","doi":"10.3390/horticulturae7070191","title":"Fertilization and Soil Nutrients Impact Differentially Cranberry Yield and Quality in Eastern Canada","year":2021,"lang":"en","type":"article","venue":"Horticulturae","topic":"Berry genetics and cultivation research","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Berry; Human fertilization; Nutrient; Yield (engineering); Anthocyanin; Cultivar; Fertilizer; Brix; Agronomy; Horticulture; Crop yield; Chemistry; Biology; Food science; Sugar","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0002556905,0.0003324496,0.0002182314,0.0002462465,0.0005835746,0.0005986693,0.0005084412,0.0001873351,0.0007389529],"category_scores_gemma":[0.0005438125,0.0001762178,0.0002410188,0.0002803058,0.0003782336,0.0001768136,0.0002219044,0.0001771106,0.00009066941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01285652,"about_ca_system_score_gemma":0.0054779,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9745285,"about_ca_topic_score_gemma":0.9862601,"domain_scores_codex":[0.9998274,0.00001977082,0.000007118342,0.00005474407,0.00003499756,0.00005587749],"domain_scores_gemma":[0.9995926,0.00009484262,0.0000493363,0.00002096383,0.0001538536,0.00008843045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001012263,0.0002162547,0.8846161,0.0000707095,0.0001816553,0.0002858011,0.0006053768,0.01703333,0.07891178,0.0003429301,0.0006680078,0.01605566],"study_design_scores_gemma":[0.00002046481,0.0001343758,0.9808387,0.000005458222,0.0000439883,0.00003309662,0.0004593375,0.01466493,0.003039506,0.00004481946,0.0006994358,0.0000158806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994735,0.00003424029,0.00008879096,0.000009313429,4.935028e-7,0.00000598841,0.0001462054,0.00000681216,0.0002347107],"genre_scores_gemma":[0.9983971,0.00004538788,0.0003305248,0.00001463729,3.304546e-7,0.000006481268,0.0003720992,0.000005294247,0.0008283061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02547151,"threshold_uncertainty_score":0.09328103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04878530277046928,"score_gpt":0.2791671271633765,"score_spread":0.2303818243929072,"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."}}