{"id":"W4214709201","doi":"10.1101/2022.02.25.482047","title":"Rapid weed adaptation and range expansion in response to agriculture over the last two centuries","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Weed Control and Herbicide Applications","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Weed; Agriculture; Selection (genetic algorithm); Range (aeronautics); Geography; Biology; Adaptation (eye); Agroforestry; Ecology; Computer science","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":[0.0003562914,0.00007939004,0.0001478958,0.0004434843,0.0003196674,0.0004092467,0.0001356959,0.0002950418,0.002923873],"category_scores_gemma":[0.0008107361,0.00006531766,0.0001081423,0.0005302062,0.0003366235,0.0002732588,0.0004417622,0.0003679237,0.000345279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003099857,"about_ca_system_score_gemma":0.0001221387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001917379,"about_ca_topic_score_gemma":0.005799691,"domain_scores_codex":[0.9998356,0.00002193904,0.000007089729,0.00006994116,0.00003872402,0.00002676623],"domain_scores_gemma":[0.9996859,0.00006630256,0.000123615,0.00002316588,0.00004607388,0.00005497335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007874022,0.0001317258,0.6062242,0.0004269751,0.0002014248,0.001262593,0.003426989,0.002011188,0.2546875,0.004916596,0.008314923,0.1176086],"study_design_scores_gemma":[0.000009093867,0.00005097777,0.9855467,0.00002081573,0.00001717803,0.0002813305,0.0005298691,0.0003893728,0.002055299,0.0006759253,0.01041043,0.00001287162],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930956,0.001513011,0.0008111753,0.0006772968,0.00005745879,0.000003736115,0.0005638031,0.00003098228,0.003246978],"genre_scores_gemma":[0.9970824,0.0005783873,0.0003958767,0.0001511321,0.00004620759,0.000004307372,0.0003279087,0.00001598377,0.00139787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002923873,"threshold_uncertainty_score":0.009781361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622367630310544,"score_gpt":0.2106739308808481,"score_spread":0.1944502545777426,"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."}}