{"id":"W4412587948","doi":"10.3390/plants14152263","title":"High-Throughput DNA Extraction Using Robotic Automation (RoboCTAB) for Large-Scale Genotyping","year":2025,"lang":"en","type":"article","venue":"Plants","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Genome Canada","keywords":"DNA extraction; Genotyping; Computer science; Scale (ratio); Scalability; Automation; Process engineering; Biology; Database; Engineering; Polymerase chain reaction; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00009371528,0.00007722421,0.0001039753,0.00001270186,0.0003363645,0.0000432522,0.0000753907,0.00007138661,0.0001123936],"category_scores_gemma":[0.00002407806,0.00003622856,0.00004512033,0.000141693,0.000006610273,0.00008922733,0.0000250983,0.00003934609,0.00001723927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000347013,"about_ca_system_score_gemma":0.00001087289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001604247,"about_ca_topic_score_gemma":0.0008291323,"domain_scores_codex":[0.9993781,0.00002240748,0.0001524369,0.0001851954,0.00007382849,0.0001879595],"domain_scores_gemma":[0.9997231,0.0001217792,0.000058389,0.00003436842,0.00003409944,0.00002827662],"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":[0.00003058049,0.0001513941,0.002638197,0.00002763751,0.00003284202,9.144275e-7,0.0001428749,0.003192387,0.9726178,0.002453229,0.0003532593,0.0183589],"study_design_scores_gemma":[0.0008650626,0.0001318454,0.6754873,0.0001961337,0.000122635,0.00002030407,0.0004721267,0.2454007,0.04277106,0.01612737,0.01793841,0.0004670077],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820135,0.00008978973,0.016031,0.0006928886,0.0005770256,0.0002646863,0.00009694624,0.00006707517,0.0001670876],"genre_scores_gemma":[0.9940596,0.00001498687,0.005078114,0.0001355107,0.0001988005,0.00001706268,0.0001961189,6.432792e-7,0.0002992025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9298467,"threshold_uncertainty_score":0.2587077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02689258971985739,"score_gpt":0.2661305686359239,"score_spread":0.2392379789160665,"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."}}