{"id":"W2136225092","doi":"10.21273/hortsci.38.7.1385","title":"A Scanner-based Root Image Acquisition Technique for Measuring Roots on a Rhizotron Window","year":2003,"lang":"en","type":"article","venue":"HortScience","topic":"Plant nutrient uptake and metabolism","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Scanner; Transplanting; Root (linguistics); Malus; Data acquisition; Computer vision; Artificial intelligence; Apple tree; Mathematics; Computer science; Computer graphics (images); Horticulture; Biology","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":[0.0006725478,0.0001483533,0.0001511652,0.00003134734,0.0003505176,0.00008365543,0.0002402019,0.00007279087,0.00005998025],"category_scores_gemma":[0.0001354586,0.00006206361,0.0001007232,0.0004249324,0.00007275831,0.0001940853,0.00001394583,0.00008097092,0.00001849289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003097951,"about_ca_system_score_gemma":0.00002620267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001952696,"about_ca_topic_score_gemma":0.00006047549,"domain_scores_codex":[0.9986157,0.00005856072,0.0001623086,0.0004188702,0.0003211728,0.0004233961],"domain_scores_gemma":[0.9995162,0.000116093,0.00007820714,0.00008193216,0.00007958569,0.0001279154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003403121,0.0000950331,0.001084453,0.000003126155,0.000001152454,0.000003570354,0.000006409548,0.00001603638,0.9905277,0.001729329,0.000287138,0.006212014],"study_design_scores_gemma":[0.0002741754,0.000430571,0.07771653,0.00006839957,0.00001136269,0.00001467031,0.00002816796,0.00007817452,0.8276534,0.001066582,0.0923592,0.0002987761],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934389,0.0001449018,0.002212936,0.0003162923,0.0001899885,0.0007290243,0.0000582798,0.00009439352,0.002815304],"genre_scores_gemma":[0.9979672,0.00001214382,0.00123921,0.0002903448,0.0001013243,0.0001905989,0.00002393501,0.000001203219,0.0001740245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1628743,"threshold_uncertainty_score":0.2695934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322479349099735,"score_gpt":0.2236664766958145,"score_spread":0.2004416832048171,"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."}}