{"id":"W4251674173","doi":"10.1515/iupac.81.0837","title":"Sorption Constant","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Electrostatics and Colloid Interactions","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Sorption; Sampling (signal processing); Computer science; Environmental chemistry; Environmental science; Chemistry; Data mining; Philosophy; 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":[0.0001456571,0.0003704634,0.000422877,0.0001158867,0.0001389076,0.00009280193,0.0003100556,0.0003433404,0.03060252],"category_scores_gemma":[0.0002683592,0.0002968977,0.0001889963,0.00009715236,0.0001066507,0.00007674105,0.00008599072,0.0005878368,0.000008431544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006973591,"about_ca_system_score_gemma":0.0008723623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007894329,"about_ca_topic_score_gemma":0.0006904129,"domain_scores_codex":[0.9979611,0.00001902985,0.0004637668,0.0004181434,0.0007276952,0.0004102399],"domain_scores_gemma":[0.9982605,0.0001150706,0.0003101511,0.000708053,0.0004663894,0.000139864],"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":[0.0001054494,0.0001839456,0.00000178892,0.0001256593,0.0001303089,0.00003301542,0.000004203491,2.723737e-7,0.003014527,0.00006541538,0.9945723,0.00176312],"study_design_scores_gemma":[0.0006163742,0.0000767801,3.441546e-7,0.0004598833,0.0001208358,0.00003472724,0.00002786305,0.000008202358,0.00139636,0.0004778861,0.9964009,0.000379872],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001566922,0.0003200347,0.0001155167,0.0004408344,0.0004457427,0.00007634702,0.9971188,0.00007940293,0.001246596],"genre_scores_gemma":[0.00007643948,0.001492179,0.00001911096,0.0001674031,0.0008010268,0.0000258673,0.9934928,0.00004012171,0.003885018],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03059409,"threshold_uncertainty_score":0.9999483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01004766707403988,"score_gpt":0.3816905959422225,"score_spread":0.3716429288681827,"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."}}