{"id":"W2046932494","doi":"10.1016/j.jala.2008.12.010","title":"Rapid ID Technology (RIDT) in Plants: High-Speed DNA Fingerprinting in Grain Seeds for the Identification, Segregation, Purity, and Traceability of Varieties Using Labautomation Robotics","year":2009,"lang":"en","type":"article","venue":"JALA Journal of the Association for Laboratory Automation","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Traceability; DNA profiling; Consumables; Biotechnology; Phenomics; Identification (biology); Fingerprint (computing); DNA extraction; Biology; Computer science; Artificial intelligence; DNA; Genomics; Polymerase chain reaction; Genetics; Botany; Genome; Business","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002734847,0.00007514614,0.000183321,0.00006734723,0.0001715437,0.00004539214,0.0001548687,0.0001556412,0.000001521487],"category_scores_gemma":[0.0008553701,0.00003407049,0.00005048522,0.0004710737,0.000037911,0.0001816273,0.00001490913,0.0001082635,8.073504e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001074492,"about_ca_system_score_gemma":0.00003504134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001001443,"about_ca_topic_score_gemma":0.0001072038,"domain_scores_codex":[0.9988064,0.0001702337,0.0006435236,0.0000948434,0.0001676383,0.0001173874],"domain_scores_gemma":[0.9979347,0.0004416846,0.001092705,0.00005079522,0.000467433,0.00001267854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00009961532,0.0002676008,0.1276105,0.0000581513,0.00004977913,2.776989e-7,0.001837727,0.007534723,0.8213568,0.008284948,0.0001942406,0.03270563],"study_design_scores_gemma":[0.0005074639,0.0001413898,0.9287617,0.00004584143,0.00003604772,0.000002784575,0.0005951193,0.02229124,0.02027043,0.02711089,0.000157119,0.000079955],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928992,0.0002318655,0.0002448994,0.005970486,0.0002127436,0.0003794701,0.00004700066,0.00001203606,0.000002278746],"genre_scores_gemma":[0.9991105,0.00005058664,0.0006966267,0.00005009921,0.00006727746,0.000004462285,0.000012159,0.000001031481,0.000007298016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8011512,"threshold_uncertainty_score":0.1389354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01234885432873449,"score_gpt":0.2305795583236299,"score_spread":0.2182307039948955,"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."}}