{"id":"W4249828958","doi":"10.1515/iupac.78.0455","title":"Partition Coefficient","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; Chemical nomenclature; Computer science; Relation (database); Partition (number theory); Management science; Data science; Chemistry; Engineering; Data mining; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001045818,0.001999094,0.001901753,0.00553045,0.0008282196,0.003057299,0.002776467,0.001530711,0.09887959],"category_scores_gemma":[0.008707976,0.000536497,0.002082964,0.008046216,0.0003568861,0.002553618,0.00146628,0.001950125,0.09852909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002235228,"about_ca_system_score_gemma":0.002162788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02131371,"about_ca_topic_score_gemma":0.02935017,"domain_scores_codex":[0.9985226,0.0001735883,0.0002479757,0.0005770226,0.0003505339,0.0001282933],"domain_scores_gemma":[0.9970215,0.001076873,0.0004562385,0.0005583119,0.0007550062,0.0001319997],"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":[0.000177513,0.00003936607,0.003462976,0.002453877,0.0001252535,0.00003097709,0.0000321451,0.0008182875,0.0002186196,0.001621878,0.9799511,0.01106802],"study_design_scores_gemma":[0.0002779214,0.00003586632,0.01083289,0.0007615502,0.0001108145,0.000150655,0.00007257838,0.0008680106,0.0004492278,0.004129924,0.9822498,0.00006077611],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002150866,0.0003886406,0.0001023825,0.00005763835,0.0000231627,0.00001558528,0.9979343,0.0001905809,0.001072658],"genre_scores_gemma":[0.001233283,0.0003796225,0.0004212772,0.00008222841,0.00001422997,0.0001201313,0.9966193,0.00008439085,0.001045475],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09887959,"threshold_uncertainty_score":0.3307852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01188027575269132,"score_gpt":0.3484418230986437,"score_spread":0.3365615473459524,"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."}}