{"id":"W4403335125","doi":"10.1002/csan.21420","title":"2024 Western Society of Crop Science Meeting Recap","year":2024,"lang":"en","type":"article","venue":"CSA News","topic":"Agricultural Productivity and Crop Improvement","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crop; Geography; Political science; Forestry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003484164,0.0001036413,0.0001168093,0.000006402569,0.0002086001,0.0001502652,0.0002614785,0.00004567175,0.0001850702],"category_scores_gemma":[0.00002420629,0.00003201166,0.0001189204,0.000666011,0.0002169824,0.0003039927,0.0001490716,0.0001182535,0.00006023452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003398435,"about_ca_system_score_gemma":0.00001834281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003814518,"about_ca_topic_score_gemma":0.0001288321,"domain_scores_codex":[0.9989199,0.00001765993,0.0001735706,0.0003736716,0.0002692541,0.0002459476],"domain_scores_gemma":[0.9997172,0.00005080557,0.0000450654,0.00005522782,0.0000659247,0.00006577785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000002345205,0.00002385234,0.0007060305,0.00002872787,0.00000682363,7.707027e-7,0.0002171518,0.000004636029,0.8939512,0.0001013507,0.007491716,0.09746533],"study_design_scores_gemma":[0.00009115207,0.0004405564,0.04100114,0.000291947,0.00003471569,0.00001622308,0.00275945,0.0002890117,0.5551171,0.0009441749,0.3985377,0.0004768193],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901308,0.0007731697,0.000005235976,0.005334111,0.0004767641,0.0001366276,0.00001068258,0.00007483111,0.003057715],"genre_scores_gemma":[0.9931973,0.0001138153,0.0001298577,0.000215555,0.0005007461,0.000006297221,0.000005241552,6.107832e-7,0.005830598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.391046,"threshold_uncertainty_score":0.2026389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02647449941825016,"score_gpt":0.2448620169445574,"score_spread":0.2183875175263073,"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."}}