{"id":"W4404494918","doi":"10.3389/frsen.2024.1414540","title":"Remote estimation of leaf nitrogen content, leaf area, and berry yield in wild blueberries","year":2024,"lang":"en","type":"article","venue":"Frontiers in Remote Sensing","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Community College; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Berry; Yield (engineering); Nitrogen; Horticulture; Vaccinium; Ericaceae; Botany; Biology; Chemistry; 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":[0.0002459164,0.0001385107,0.0002847954,0.00008362491,0.0000606943,0.00003454412,0.00008810698,0.0002117563,0.000007361233],"category_scores_gemma":[0.0001269196,0.00007069291,0.00005382847,0.0003539253,0.0001687427,0.0001259881,0.00004878788,0.0002520855,0.00000202439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004022979,"about_ca_system_score_gemma":0.000007746752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001639884,"about_ca_topic_score_gemma":0.003742703,"domain_scores_codex":[0.9990226,0.00004528392,0.0002942763,0.0002880909,0.0001013385,0.0002483951],"domain_scores_gemma":[0.9996828,0.0001332012,0.00006193944,0.00006699556,0.0000223213,0.00003276634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005749299,0.000008381036,0.007752429,0.00003327425,0.00002066549,0.00005962619,0.0002662048,0.00004080813,0.02328817,0.00005145157,0.0003361324,0.9680853],"study_design_scores_gemma":[0.0008460254,0.000356463,0.0558896,0.002591712,0.0001019944,0.0002125372,0.008429756,0.8399274,0.01987999,0.06973421,0.001250652,0.0007797119],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930098,0.002476695,0.001604858,0.00197585,0.0002776122,0.0001822031,0.000007420098,0.0001122365,0.0003533202],"genre_scores_gemma":[0.9927781,0.0002397515,0.006781528,0.00008184463,0.00002842939,8.87761e-8,0.00001023522,0.000002202818,0.00007780494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9673057,"threshold_uncertainty_score":0.2882773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02633322822188332,"score_gpt":0.2200622820372514,"score_spread":0.193729053815368,"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."}}