{"id":"W4242872072","doi":"10.1515/iupac.80.0180","title":"Standard Molality","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Terminology; Glossary; Confusion; Molality; Chemical nomenclature; Solubility; Diversity (politics); Chemistry; Epistemology; Philosophy; Political science; Organic chemistry; Law; Linguistics; Psychology; Aqueous solution","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":[0.001392548,0.002074457,0.001702364,0.005966173,0.001134507,0.00352677,0.00415202,0.001934958,0.06504607],"category_scores_gemma":[0.01089025,0.0006975689,0.002035114,0.009103687,0.0006241683,0.00382234,0.002645906,0.00279277,0.1122619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001573699,"about_ca_system_score_gemma":0.002534952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0127574,"about_ca_topic_score_gemma":0.02301627,"domain_scores_codex":[0.9980057,0.0002768026,0.0003570616,0.0006667916,0.0004738241,0.0002197926],"domain_scores_gemma":[0.9966341,0.000750625,0.0004090171,0.0009980601,0.001003908,0.0002042243],"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":[0.0001632164,0.00003422891,0.002498633,0.00125022,0.00005615267,0.00004495848,0.00004561994,0.0004998303,0.000200144,0.001751334,0.9860566,0.007399152],"study_design_scores_gemma":[0.0001222543,0.00001465802,0.003419349,0.0003194653,0.00002486735,0.00007795993,0.00008406277,0.0003268682,0.0003275682,0.002608512,0.9926427,0.00003177091],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002712082,0.0001471083,0.0001599845,0.0000840563,0.0000446326,0.00002055548,0.9973618,0.0005063984,0.001404177],"genre_scores_gemma":[0.0005516324,0.0001361185,0.0005044565,0.00006835135,0.00001332459,0.00008711942,0.9977288,0.0001153056,0.0007949747],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06504607,"threshold_uncertainty_score":0.2176008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471090664215349,"score_gpt":0.3976734607200029,"score_spread":0.3829625540778494,"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."}}