{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008140827,0.002233126,0.001808471,0.003115556,0.001050299,0.003548978,0.002610445,0.001786831,0.07514761],"category_scores_gemma":[0.005371228,0.0006772462,0.00205079,0.005492451,0.0003544487,0.003506908,0.001426009,0.002289066,0.1336257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001903377,"about_ca_system_score_gemma":0.002386483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02202026,"about_ca_topic_score_gemma":0.03510235,"domain_scores_codex":[0.9983021,0.0001615508,0.0002006841,0.0006809526,0.0004682346,0.0001864486],"domain_scores_gemma":[0.9980025,0.0004838683,0.0002562753,0.000511479,0.0006321202,0.000113775],"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":[0.0002432077,0.00006116623,0.007326607,0.002606602,0.0001682919,0.00005821751,0.00004337476,0.001857014,0.000689631,0.002244359,0.9652625,0.01943902],"study_design_scores_gemma":[0.0001207044,0.00002082372,0.006653021,0.0002493653,0.00006190882,0.0001234561,0.0000590139,0.0009709092,0.0008321655,0.002740627,0.9881265,0.00004145998],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005109857,0.0004118205,0.0002046232,0.00009576223,0.00004681736,0.00001399217,0.9948093,0.0006366362,0.003270166],"genre_scores_gemma":[0.002390499,0.0004044252,0.0006153169,0.0001129234,0.00001627227,0.0000582078,0.9937184,0.0001652979,0.002518682],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07514761,"threshold_uncertainty_score":0.2513938,"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."}}