{"id":"W4256491651","doi":"10.1515/iupac.88.0291","title":"Solvent Desorption","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Process Optimization and Integration","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Extraction (chemistry); Computer science; Process engineering; Solvent extraction; Sample preparation; Sample (material); Chromatography; Biochemical engineering; Chemistry; Engineering","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":[0.0001677706,0.0002756354,0.0002915378,0.0001466153,0.0001116167,0.000153137,0.0003153987,0.0003043443,0.001306935],"category_scores_gemma":[0.0001910197,0.0002628567,0.00008654814,0.00005755176,0.00003962146,0.0001869786,0.00003354942,0.0003714131,0.00000794985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003053755,"about_ca_system_score_gemma":0.0001576947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002230444,"about_ca_topic_score_gemma":0.0004867875,"domain_scores_codex":[0.998861,0.00001254674,0.0002764839,0.0001989567,0.0004480645,0.0002030134],"domain_scores_gemma":[0.9989871,0.000009355853,0.0001112496,0.000532982,0.0002754409,0.00008384226],"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":[0.00001111261,0.00003332388,6.243225e-7,0.0001516363,0.00003690878,0.00000467223,0.000006470884,0.003372318,0.0000110429,0.000003957881,0.994343,0.002024942],"study_design_scores_gemma":[0.000253506,0.00003821239,0.000005426344,0.0001825078,0.00004745943,0.000004029142,0.000006281673,0.01016326,0.00006326279,0.00004555702,0.9889176,0.0002728415],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001493038,0.000725493,0.01147475,0.00005854119,0.001025317,0.0001460303,0.9861701,0.0002150147,0.0001698528],"genre_scores_gemma":[0.00007377256,0.002769555,0.0001803428,0.00005733052,0.000440543,0.0000167014,0.9962262,0.00003631474,0.0001992443],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01129441,"threshold_uncertainty_score":0.9999824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463492362922162,"score_gpt":0.3840467796609045,"score_spread":0.3694118560316829,"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."}}