{"id":"W6976638025","doi":"10.60692/nk8me-jp437","title":"The International Weed Genomics Consortium: Community Resources for Weed Genomics Research","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Agriculture, Land Use, Rural Development","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Genomics; Weed; Agriculture; Weed control; Variety (cybernetics); Sustainable agriculture","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":[0.01587623,0.001361827,0.001768848,0.00918518,0.002816731,0.004949227,0.003980043,0.001504026,0.07842569],"category_scores_gemma":[0.01793932,0.0008499253,0.0006403204,0.01579952,0.0007624057,0.002626761,0.007386546,0.002765024,0.03655911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0018998,"about_ca_system_score_gemma":0.01545493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02258208,"about_ca_topic_score_gemma":0.03096961,"domain_scores_codex":[0.9962323,0.0008662199,0.000308267,0.00057316,0.001389138,0.0006308365],"domain_scores_gemma":[0.9753606,0.003419152,0.001466157,0.003713206,0.006390804,0.009650131],"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":[0.0007677727,0.0003063104,0.003952526,0.001032696,0.00007397881,0.0001895992,0.0008091339,0.0004887258,0.01693789,0.009873305,0.8349819,0.1305862],"study_design_scores_gemma":[0.0004170575,0.00008622304,0.01003049,0.00053776,0.00006938001,0.00009020865,0.0003318672,0.001533043,0.003029588,0.006537667,0.9772281,0.0001084823],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01643514,0.004590656,0.07186829,0.01795281,0.001607783,0.003995966,0.6895829,0.04907328,0.1448932],"genre_scores_gemma":[0.02128728,0.001718045,0.1407218,0.002068177,0.0004027633,0.003787955,0.7924731,0.009203225,0.02833757],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.07842569,"threshold_uncertainty_score":0.2623601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1114778856871571,"score_gpt":0.2581479883047103,"score_spread":0.1466701026175532,"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."}}