{"id":"W1561510931","doi":"10.1002/ieam.1473","title":"Predicted no effect concentration derivation as a significant source of variability in environmental hazard assessments of chemicals in aquatic systems: An international analysis","year":2013,"lang":"en","type":"article","venue":"Integrated Environmental Assessment and Management","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Hazard; Environmental science; Scope (computer science); European union; Environmental health; Environmental resource management; Environmental planning; Computer science; Business; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03134772,0.0006492359,0.0006881125,0.001923588,0.0005541792,0.002072792,0.00121105,0.0008379698,0.000854987],"category_scores_gemma":[0.06160181,0.0003618338,0.001549836,0.00170325,0.001530244,0.001649251,0.001795826,0.00189093,0.000158255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001524229,"about_ca_system_score_gemma":0.001674426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002948982,"about_ca_topic_score_gemma":0.001701659,"domain_scores_codex":[0.9712964,0.01259367,0.001771718,0.004182955,0.009772273,0.0003831078],"domain_scores_gemma":[0.9077986,0.07153355,0.005888304,0.00813996,0.006452,0.0001875995],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0009355659,0.0003896045,0.3015718,0.001919027,0.002903986,0.001089368,0.001823571,0.3098058,0.02014394,0.09118939,0.008826025,0.2594019],"study_design_scores_gemma":[0.0001593279,0.001570984,0.3253803,0.0008668138,0.001694878,0.002350122,0.001224434,0.3941999,0.0786313,0.1341893,0.05938448,0.0003482584],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.309199,0.008388169,0.6391004,0.002763669,0.0003581086,0.0007610446,0.003348245,0.0006539067,0.03542747],"genre_scores_gemma":[0.9478704,0.001125064,0.04654617,0.0004892244,0.0000725879,0.0003852654,0.002381026,0.0001199732,0.001010308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9686523,"threshold_uncertainty_score":0.1657846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00485408538535816,"score_gpt":0.2490959853975744,"score_spread":0.2442419000122162,"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."}}