{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007201078,0.00008682451,0.0001167508,0.000004477767,0.00008953185,0.0001005561,0.0000486566,0.00005121999,0.0001896766],"category_scores_gemma":[0.00009065055,0.00003328218,0.00002078007,0.0001820426,0.00002417333,0.00005381458,0.00006360707,0.00007343009,9.551197e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002677455,"about_ca_system_score_gemma":0.00003150899,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1401289,"about_ca_topic_score_gemma":0.8410378,"domain_scores_codex":[0.9991696,0.00005486713,0.0001746975,0.0002163536,0.0002056394,0.0001787982],"domain_scores_gemma":[0.9996532,0.00006555187,0.00003478916,0.00003299732,0.0001013269,0.0001121632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002252912,0.00005998633,0.6009728,0.00001133193,0.00001051117,0.000006513944,0.0001049073,0.000005802198,0.3838247,0.00003718307,0.0001462555,0.01479746],"study_design_scores_gemma":[0.0001332684,0.00002819409,0.9917378,0.00001730831,0.000002992199,0.000002791515,0.0004284483,0.00009907452,0.007097982,0.00003626747,0.0003235344,0.00009233214],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984741,0.0003424607,0.000001164132,0.000838412,0.00003217093,0.00008537904,0.0000203756,0.000006526675,0.0001994115],"genre_scores_gemma":[0.9991634,0.0001506382,0.000003671315,0.0001128306,0.00003096652,0.000006350789,0.00005626594,5.363722e-7,0.0004753219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7009088,"threshold_uncertainty_score":0.865597,"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."}}