{"id":"W4404329248","doi":"10.1111/wre.12669","title":"Site‐specific weed management on organic grain farms using variable rate seeding and data driven simulation","year":2024,"lang":"en","type":"article","venue":"Weed Research","topic":"Weed Control and Herbicide Applications","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Conservation Service; Western SARE","keywords":"Seeding; Weed control; Weed; Agronomy; Variable (mathematics); Environmental science; Agricultural engineering; Mathematics; Biology; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007467705,0.0005127205,0.0003737985,0.0003913047,0.0003422672,0.0005030861,0.0007248112,0.0005198201,0.0008872621],"category_scores_gemma":[0.001171155,0.0002732211,0.000356606,0.0003979861,0.0003408042,0.0003491394,0.0003107044,0.0003548598,0.00007256174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001621708,"about_ca_system_score_gemma":0.001072724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06458099,"about_ca_topic_score_gemma":0.0636807,"domain_scores_codex":[0.9998316,0.00005626455,0.000007499235,0.00003671095,0.00002454055,0.00004335573],"domain_scores_gemma":[0.998793,0.0008001456,0.0001192894,0.00006341506,0.0001220452,0.0001020092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007542712,0.00007534099,0.005517416,0.000009047572,0.00001199697,0.0000251189,0.00001216166,0.9921255,0.0004745961,0.00008655913,0.00005510824,0.001531825],"study_design_scores_gemma":[0.00002470028,0.0000728604,0.00222728,0.000001626017,0.000006483785,0.000002241091,0.00002053292,0.9971687,0.0003151605,0.00008287941,0.00007154096,0.000005984375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957845,0.00001798182,0.00270598,0.00003467499,0.000005180375,0.00003430937,0.0001812582,0.0000857146,0.001150377],"genre_scores_gemma":[0.9978629,0.00001173654,0.001806964,0.000006907692,9.62692e-7,0.00001791241,0.0001122745,0.00000484401,0.000175526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06458099,"threshold_uncertainty_score":0.1284102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1690617307155778,"score_gpt":0.3746286865593194,"score_spread":0.2055669558437416,"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."}}