{"id":"W4413024583","doi":"10.1002/ppj2.70034","title":"Affordable phenomics: Expanding access to enhancing genetic gain in plant breeding","year":2025,"lang":"en","type":"article","venue":"The Plant Phenome Journal","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lethbridge College; Agriculture and Agri-Food Canada; McGill University","funders":"Agriculture and Agri-Food Canada; Kirkhouse Trust; United States Agency for International Development; National Science Foundation","keywords":"Phenomics; Biotechnology; Genetic gain; Computer science; Biology; Medicine; Genetic variation; Environmental health; Genetics; Genomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005573169,0.0006722625,0.0009295651,0.001913967,0.0003736877,0.001842426,0.002223725,0.0009956193,0.01067809],"category_scores_gemma":[0.00503458,0.0005005963,0.0005552261,0.001973697,0.0007951163,0.003582184,0.003930287,0.001840612,0.002566664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008127731,"about_ca_system_score_gemma":0.0009342071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009935787,"about_ca_topic_score_gemma":0.001683012,"domain_scores_codex":[0.9981261,0.0005657513,0.00008074964,0.0003237686,0.0007272862,0.0001763553],"domain_scores_gemma":[0.9955225,0.002089562,0.0005078529,0.0005792282,0.0009252482,0.0003757087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004495803,0.0001747112,0.007611225,0.002772258,0.0001641738,0.0003530641,0.0003926436,0.004089192,0.1579787,0.05338227,0.02763484,0.7449973],"study_design_scores_gemma":[0.0002637662,0.001324128,0.04753612,0.001747002,0.0003221007,0.001498793,0.0007365812,0.01995001,0.08296047,0.08815798,0.7552057,0.0002972979],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08348738,0.06248284,0.7630723,0.02008791,0.001636079,0.0005201633,0.003699983,0.006898715,0.05811471],"genre_scores_gemma":[0.2892681,0.0705657,0.6153307,0.005272476,0.001268853,0.001085196,0.004342471,0.001503901,0.01136265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01067809,"threshold_uncertainty_score":0.03572172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03912880358489513,"score_gpt":0.2690318749659285,"score_spread":0.2299030713810333,"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."}}