{"id":"W4401511204","doi":"10.3389/fpls.2024.1417912","title":"Harnessing the power of machine learning for crop improvement and sustainable production","year":2024,"lang":"en","type":"review","venue":"Frontiers in Plant Science","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo; Bill and Melinda Gates Foundation","keywords":"Machine learning; Computer science; Artificial intelligence; Principal (computer security); Production (economics); Crop production; Predictive power; Data science; Agriculture","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001007404,0.0006570074,0.0007957148,0.002132885,0.0002703956,0.001424529,0.0007038148,0.00133976,0.002257709],"category_scores_gemma":[0.001393776,0.0002207867,0.0005466627,0.002236165,0.0009468447,0.002431442,0.0008020775,0.002195346,0.001271134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007773678,"about_ca_system_score_gemma":0.0009713221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009970892,"about_ca_topic_score_gemma":0.001366626,"domain_scores_codex":[0.9996688,0.00009899103,0.00002380983,0.00006003531,0.0001271025,0.00002119818],"domain_scores_gemma":[0.9989728,0.0007731818,0.00005716465,0.00003670665,0.0001323106,0.00002790261],"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":[0.00002511375,0.00005565388,0.0003014134,0.01174738,0.0001175553,0.0001368623,0.0001226464,0.002036306,0.001807815,0.05184028,0.01189379,0.9199153],"study_design_scores_gemma":[0.00000766998,0.0001027285,0.001065598,0.005141027,0.00009795437,0.0005181682,0.000160402,0.001221158,0.001358845,0.04100224,0.9492834,0.00004096025],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004088602,0.9889031,0.003500441,0.001831984,0.0002850003,0.000008573898,0.00002484624,0.00002530711,0.005011837],"genre_scores_gemma":[0.005488424,0.9896387,0.002769662,0.0005897919,0.0003783548,0.00001315667,0.00003368636,0.00000709998,0.001081067],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002257709,"threshold_uncertainty_score":0.007552803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01549929262326074,"score_gpt":0.2431627198203118,"score_spread":0.2276634271970511,"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."}}