{"id":"W4384207444","doi":"10.1002/csc2.21054","title":"Crop Science","year":2023,"lang":"en","type":"article","venue":"Crop Science","topic":"Agricultural Productivity and Crop Improvement","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Agricultural Center, Louisiana State University; University of Agriculture, Faisalabad; South Australian Research and Development Institute; Universidad de Buenos Aires; College of Engineering, Michigan State University; Chinese Academy of Agricultural Sciences; Chinese Academy of Sciences; University of Jinan; Clemson University; Teagasc; University of Wisconsin-Madison; Universidad Nacional de Rosario; Louisiana State University; University of Illinois at Urbana-Champaign; Auburn University; Michigan State University; Universität Hohenheim; Oklahoma State University; University of Minnesota; China Agricultural University; University of Missouri; Punjab Agricultural University; McGill University; North Carolina State University; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences; Purdue University; Agricultural Research Service; Cotton Incorporated; Oregon State University; City University of New York; U.S. Department of Agriculture","keywords":"Citation; Crop; Biology; Library science; Computer science; Agronomy","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001574649,0.0001463771,0.0001211153,0.00005299992,0.002278917,0.0005125313,0.001364967,0.0000351085,0.0002232765],"category_scores_gemma":[0.0003137762,0.00004810637,0.00005295884,0.007261122,0.002698129,0.001111707,0.0005821268,0.0001265515,0.001035964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000927159,"about_ca_system_score_gemma":0.00008853087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001429196,"about_ca_topic_score_gemma":0.00004505998,"domain_scores_codex":[0.9973421,0.00001757275,0.0001729091,0.0006767641,0.0009333994,0.0008572216],"domain_scores_gemma":[0.9991956,0.00004627939,0.00007069842,0.0001441487,0.0002811052,0.000262142],"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":[0.000002805476,0.00002624262,0.000542159,0.000001928855,6.67343e-7,0.000002813016,0.0001159497,0.00001933969,0.9377326,0.001064989,0.0009474484,0.0595431],"study_design_scores_gemma":[0.000100854,0.0002971528,0.5629672,0.00001869483,0.000005396426,0.00001761883,0.001246358,0.0004673272,0.3998906,0.00164196,0.03287251,0.0004743169],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907963,0.00002806322,0.000003390936,0.003734616,0.0005324909,0.0001962326,0.000008168038,0.0002960406,0.004404753],"genre_scores_gemma":[0.9969792,0.00001765926,0.00004584268,0.0002928531,0.0002710921,0.00001360525,0.000004604139,5.611545e-7,0.002374552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.562425,"threshold_uncertainty_score":0.9997419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02985536651302706,"score_gpt":0.2479006136462046,"score_spread":0.2180452471331775,"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."}}