{"id":"W2937027379","doi":"10.2903/j.efsa.2019.5660","title":"Setting an import tolerance for 2,4‐D in soyabeans","year":2019,"lang":"en","type":"article","venue":"EFSA Journal","topic":"Genetically Modified Organisms Research","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metabolite; Residue (chemistry); Biotechnology; Biology; Agricultural science; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006777869,0.00007095703,0.0001063267,0.00001343608,0.0001073455,0.0001034711,0.0002667254,0.00005811706,0.00113594],"category_scores_gemma":[0.00004885939,0.00002711885,0.00005163224,0.0001233667,0.00001550785,0.0001181819,0.00003313076,0.000226976,0.00004968339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002355303,"about_ca_system_score_gemma":0.0000235219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002471708,"about_ca_topic_score_gemma":0.0001648902,"domain_scores_codex":[0.9990182,0.00005548651,0.0001944779,0.000165723,0.0002123646,0.0003537354],"domain_scores_gemma":[0.9996202,0.00009882398,0.00004683005,0.00003925976,0.00006125327,0.0001336285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004153572,0.00007004046,0.1012486,0.000004674129,0.00000350726,0.000009216055,0.000105924,0.0001689318,0.8302501,0.0001085383,0.0003489911,0.06763984],"study_design_scores_gemma":[0.0005804324,0.0008296157,0.9665946,0.00003020265,0.000002597697,0.0001045214,0.0004675916,0.002193033,0.01110523,0.002172926,0.01569361,0.0002256591],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977126,0.0000533515,0.00003071642,0.001386182,0.0001285547,0.0001889846,0.000005695768,0.00001043923,0.0004835101],"genre_scores_gemma":[0.9979033,0.00001164623,0.00108961,0.0001818673,0.0003776689,0.000004505847,0.000005570263,0.000001070161,0.0004246993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.865346,"threshold_uncertainty_score":0.9997771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02004021530721093,"score_gpt":0.2646364608020363,"score_spread":0.2445962454948254,"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."}}