{"id":"W3145915006","doi":"10.1002/ps.6392","title":"East meets west: regional impact on agrochemical discovery and innovation","year":2021,"lang":"en","type":"article","venue":"Pest Management Science","topic":"Plant tissue culture and regeneration","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Greenfield Research (Canada)","funders":"","keywords":"Agrochemical; Government (linguistics); Population; Crop protection; Business; Biotechnology; Agriculture; Natural resource economics; Agricultural economics; Economics; Biology; Agroforestry; Ecology; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001110305,0.00007340607,0.00004609871,0.00006310076,0.0001160808,0.00008766903,0.0000945159,0.00002923981,0.000006091489],"category_scores_gemma":[0.00002296582,0.00005564205,0.00001625875,0.0003790817,0.0001175554,0.00001732442,0.00009621933,0.00002973531,0.000006572829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000165095,"about_ca_system_score_gemma":0.0000470066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004565707,"about_ca_topic_score_gemma":0.00001228912,"domain_scores_codex":[0.9993142,0.000008663944,0.00007752622,0.000305495,0.0001708076,0.000123282],"domain_scores_gemma":[0.9997404,0.000002053458,0.00003094095,0.0001404561,0.00005395938,0.00003225478],"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":[0.00001449935,0.00003643383,0.0007375175,0.000008251887,0.00001108328,0.000009083797,0.0000190973,0.00007176005,0.9848791,0.008624355,0.004263321,0.001325481],"study_design_scores_gemma":[0.0005468811,0.0001855913,0.0802081,0.00006088605,0.0000274019,0.0001285806,0.0001386196,0.0003190851,0.8269062,0.0002341193,0.09086995,0.0003745846],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933591,0.0002439307,0.0006246968,0.001324908,0.00007596819,0.00006244997,0.000004264851,0.000005723935,0.00429888],"genre_scores_gemma":[0.9956019,0.0001335334,0.0003293466,0.0003986665,0.0001070066,0.000004938766,0.000157511,0.000002974625,0.003264129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1579729,"threshold_uncertainty_score":0.2269017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01552649937130023,"score_gpt":0.2694277324049881,"score_spread":0.2539012330336878,"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."}}