{"id":"W2158948037","doi":"10.1002/ieam.1561","title":"Aquatic risk assessment of pesticides in Latin America","year":2014,"lang":"en","type":"article","venue":"Integrated Environmental Assessment and Management","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Latin Americans; Government (linguistics); Risk assessment; Environmental planning; Business; Agriculture; Pesticide; Environmental protection; Environmental resource management; Environmental science; Political science; Ecology; Computer science; Biology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005506783,0.0003351328,0.00041757,0.0001524621,0.0001578443,0.00002502052,0.0002660362,0.0001242071,0.003263734],"category_scores_gemma":[0.00001069503,0.0003058467,0.00007269777,0.0002567079,0.0006700286,0.0001992769,0.0005025502,0.0003553359,0.0001061159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005297121,"about_ca_system_score_gemma":0.000004933149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002310478,"about_ca_topic_score_gemma":0.0002156145,"domain_scores_codex":[0.997662,0.0003304438,0.000584106,0.0006142882,0.0003582598,0.00045087],"domain_scores_gemma":[0.999083,0.0001525444,0.0002877807,0.0003472448,7.68165e-7,0.0001286838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002165218,0.0007855433,0.9374686,0.00002292084,0.00006549693,0.00001538394,0.00009526494,0.004174246,0.00570147,0.0006013559,0.0003366774,0.05071134],"study_design_scores_gemma":[0.001080789,0.0005221125,0.9541295,0.00003047323,0.00008208044,0.000003534477,0.0005870606,0.03478776,0.0004376493,0.001655209,0.006364369,0.0003195203],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9319816,0.00002330894,0.008311925,0.0001621882,0.0001090395,0.0006708385,0.00001621811,0.0000329373,0.058692],"genre_scores_gemma":[0.9756016,0.0008912264,0.02206193,0.0003297449,0.00001084344,0.0001544004,0.00004936429,0.00002579459,0.0008751288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05781687,"threshold_uncertainty_score":0.9999394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006148117077100922,"score_gpt":0.246478258690338,"score_spread":0.2403301416132371,"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."}}