{"id":"W3094435510","doi":"10.3390/plants9101401","title":"Conditioning Machine Learning Models to Adjust Lowbush Blueberry Crop Management to the Local Agroecosystem","year":2020,"lang":"en","type":"article","venue":"Plants","topic":"Berry genetics and cultivation research","field":"Agricultural and Biological Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi; Agriculture and Agri-Food Canada; Université Laval","funders":"Agriculture and Agri-Food Canada","keywords":"Agroecosystem; Fertilizer; Yield (engineering); Environmental science; Growing season; Mathematics; Agronomy; Crop; Horticulture; Biology; Ecology; Physics","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":[0.0001383791,0.00008615377,0.00009037087,0.000007954818,0.0002823007,0.00009589763,0.0002648422,0.00002884823,0.0004383361],"category_scores_gemma":[0.00001023904,0.00003093198,0.00003071941,0.0002349052,0.00001051017,0.00003586075,0.0001659441,0.0001163714,0.0005616596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001436456,"about_ca_system_score_gemma":0.000002395794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001561111,"about_ca_topic_score_gemma":0.0005003165,"domain_scores_codex":[0.9990673,0.00005927453,0.0001317317,0.0002325583,0.0002773713,0.0002317588],"domain_scores_gemma":[0.9996632,0.00004713058,0.00002556779,0.00003564925,0.00003527301,0.0001931651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003489249,0.0001619496,0.005350563,0.00009587945,0.0001818302,0.0001215239,0.00447392,0.2849978,0.06427309,0.003006017,0.06515403,0.5718344],"study_design_scores_gemma":[0.0005642243,0.000894009,0.09332217,0.0001737696,0.00002660349,0.00001773827,0.009895321,0.2607047,0.004810214,0.0002161195,0.6286321,0.000743041],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813542,0.00008144852,0.001417128,0.01263204,0.0000599866,0.0004232334,0.0001132011,0.00005622653,0.003862477],"genre_scores_gemma":[0.9966428,0.00002140071,0.00006573631,0.002235462,0.0001296636,0.00003296047,0.00008666205,0.000001114863,0.0007841969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5710914,"threshold_uncertainty_score":0.7219185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0779753587184054,"score_gpt":0.2403108559895257,"score_spread":0.1623354972711203,"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."}}