{"id":"W4413384284","doi":"10.1016/j.plaphe.2025.100062","title":"Deep learning in plant phenotyping: the first ten years","year":2025,"lang":"en","type":"article","venue":"Plant Phenomics","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; National Research Council Canada","funders":"","keywords":"Biology; Artificial intelligence; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005231804,0.0008063752,0.000611243,0.0007839634,0.0005132085,0.002825893,0.0008587893,0.002554811,0.00232319],"category_scores_gemma":[0.01114144,0.0005744688,0.0003717604,0.001155689,0.002348515,0.00454321,0.002513157,0.006248048,0.001358303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002194247,"about_ca_system_score_gemma":0.001126034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003102406,"about_ca_topic_score_gemma":0.003166983,"domain_scores_codex":[0.9988796,0.0004167061,0.00008626554,0.0001712182,0.0003041967,0.00014199],"domain_scores_gemma":[0.9958844,0.002274992,0.0001859741,0.0002741246,0.0009924829,0.0003879589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004367114,0.000142341,0.002344949,0.001175491,0.0001001434,0.0001962986,0.0006821403,0.007616396,0.001883818,0.1208888,0.1052647,0.7592682],"study_design_scores_gemma":[0.00003674803,0.0002554229,0.002797837,0.002516564,0.00003978077,0.0003527493,0.000451506,0.02497553,0.003152604,0.1203984,0.8449071,0.0001158087],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01663527,0.6436699,0.1680584,0.1268753,0.02025454,0.00007738208,0.0004632059,0.0004152154,0.0235508],"genre_scores_gemma":[0.227434,0.5270158,0.1281475,0.04291863,0.03514595,0.0002445692,0.0008810568,0.0004948067,0.03771761],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005231804,"threshold_uncertainty_score":0.02766871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009503914614895321,"score_gpt":0.1770975704625845,"score_spread":0.1675936558476892,"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."}}