{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006286263,0.0001379523,0.0001701593,0.0001101996,0.0003754145,0.0002966477,0.0006528432,0.00003598789,0.007934201],"category_scores_gemma":[0.00004099483,0.0001016992,0.00004605911,0.0003782352,0.00004506957,0.0002119457,0.0003945518,0.0002648368,0.0002529587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00103328,"about_ca_system_score_gemma":0.00002139754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001765697,"about_ca_topic_score_gemma":0.001212055,"domain_scores_codex":[0.9987412,0.00005116738,0.0003350594,0.0001848017,0.0002205724,0.0004671843],"domain_scores_gemma":[0.9995275,0.00009352778,0.0000994673,0.0001520656,0.000005260448,0.0001221515],"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":[0.0007459115,0.0005229861,0.3947595,0.0001004379,0.0001603188,0.0003055379,0.01563423,0.04135088,0.4137084,0.004101367,0.1160113,0.01259908],"study_design_scores_gemma":[0.003800364,0.0003234543,0.8287185,0.0009670901,0.0001280779,0.001125007,0.04357879,0.006624807,0.02654498,0.006037289,0.08055203,0.001599601],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702098,0.0001193054,0.001970633,0.001288441,0.0004356185,0.0001853203,0.00007211992,0.00001966839,0.02569912],"genre_scores_gemma":[0.9980373,0.0002003907,0.0001071206,0.001089519,0.0001088305,0.00001331681,0.00001174688,0.000009108061,0.0004226577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.433959,"threshold_uncertainty_score":0.9929727,"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."}}