{"id":"W4249684988","doi":"10.1017/wsc.2016.30","title":"Another view","year":2017,"lang":"en","type":"article","venue":"Weed Science","topic":"Weed Control and Herbicide Applications","field":"Agricultural and Biological Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Herbicide resistance; Weed; Resistance (ecology); Weed control; Weed science; Profit (economics); Agroforestry; Business; Economics; Biology; Agronomy; Microeconomics","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":[0.002510637,0.0005293997,0.0004353601,0.0008824937,0.002961132,0.008604123,0.001399994,0.008254252,0.07825973],"category_scores_gemma":[0.006824375,0.0001768473,0.0004629269,0.0005807105,0.006301014,0.008611533,0.00391263,0.01137648,0.02263443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002662438,"about_ca_system_score_gemma":0.004159375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004119162,"about_ca_topic_score_gemma":0.004248827,"domain_scores_codex":[0.9977842,0.0004438689,0.00007197976,0.0006215061,0.0007512114,0.0003271886],"domain_scores_gemma":[0.9969712,0.0006539983,0.0001643774,0.000381876,0.001089102,0.0007394055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003196182,0.0000227651,0.0003749118,0.00009518352,0.00001099465,0.0001333308,0.0006694574,0.00005969421,0.000272634,0.3908857,0.5649052,0.04253827],"study_design_scores_gemma":[0.000005539326,0.000008208051,0.0001486592,0.0001036246,0.000003278169,0.0001238375,0.0004806164,0.00002950111,0.00008436436,0.04225426,0.9567516,0.000006550486],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001428775,0.01353398,0.003422054,0.6777328,0.0308316,0.000023719,0.0002524694,0.0001404623,0.2726341],"genre_scores_gemma":[0.06284527,0.01997162,0.003109766,0.5280384,0.03205419,0.00008667309,0.0004465965,0.0002463277,0.3532012],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.07825973,"threshold_uncertainty_score":0.2618049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0324608687805276,"score_gpt":0.2615882296306573,"score_spread":0.2291273608501296,"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."}}