{"id":"W4251159376","doi":"10.1515/iupac.78.0207","title":"Chronic Effect","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide and Herbicide Environmental Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Relation (database); Chemical nomenclature; Computer science; Field (mathematics); Pesticide; Management science; Data science; Chemistry; Engineering; Ecology; Data mining; Biology; Mathematics; Linguistics","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":[0.000429313,0.0005752529,0.0006510001,0.00004962584,0.0002268312,0.00003197154,0.000558012,0.0002924305,0.1270556],"category_scores_gemma":[0.0001650207,0.0003936334,0.0001996407,0.0001287998,0.000557192,0.0001177342,0.0008880797,0.0004108823,0.0002963641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002685883,"about_ca_system_score_gemma":0.0000571703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006643719,"about_ca_topic_score_gemma":0.003297023,"domain_scores_codex":[0.9969144,0.0001023054,0.0003770777,0.000714348,0.00124582,0.000646037],"domain_scores_gemma":[0.9987099,0.0001395642,0.0001960229,0.0007504257,0.000007558392,0.000196584],"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":[0.00004275879,0.00005939773,0.0005815,0.00005085107,0.00006265396,0.00007914148,0.000003822749,0.00001070426,0.0001488764,3.41162e-7,0.9854478,0.01351218],"study_design_scores_gemma":[0.0007185707,0.0007003912,0.002596739,0.0001773756,0.0001414371,0.0000132302,0.000002231696,0.000001459043,0.000107552,0.00006838862,0.994964,0.0005086484],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007351458,0.001414274,0.0000319373,0.0003445932,0.000419948,0.0003698152,0.9960476,0.00005755033,0.0005792063],"genre_scores_gemma":[0.00016733,0.001462644,0.00001539433,0.0002565735,0.0009838241,0.00004534579,0.9959683,0.00004309161,0.001057532],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1267593,"threshold_uncertainty_score":0.9998516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00710501626441482,"score_gpt":0.3436226243262596,"score_spread":0.3365176080618448,"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."}}