{"id":"W4365147146","doi":"10.1515/iupac.94.0542","title":"Hydration","year":2023,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Various Chemistry Research Topics","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Terminology; Abandonment (legal); Meaning (existential); Field (mathematics); Epistemology; Computer science; Linguistics; Philosophy; Mathematics; Political science","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":[0.001017468,0.002239651,0.001215879,0.002416304,0.001177268,0.002856878,0.00277798,0.001680878,0.1918699],"category_scores_gemma":[0.00506361,0.0005610901,0.001632311,0.003347597,0.0003522643,0.002789533,0.002490983,0.001908279,0.3058514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001354056,"about_ca_system_score_gemma":0.001623775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02312879,"about_ca_topic_score_gemma":0.05593377,"domain_scores_codex":[0.9987424,0.0002216982,0.0001375703,0.0004683004,0.0002742873,0.0001557823],"domain_scores_gemma":[0.9982712,0.0003325467,0.0001397223,0.0005851555,0.0005311742,0.000140151],"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":[0.00004630358,0.00001444315,0.0005239552,0.0003023205,0.00001445248,0.00001359736,0.00001680453,0.00009061366,0.00008440115,0.0004700462,0.9938526,0.004570533],"study_design_scores_gemma":[0.00007430037,0.00001144681,0.002644602,0.0002295787,0.00001612421,0.00005390132,0.00007870835,0.0002620426,0.0002190854,0.001688356,0.9946985,0.00002329523],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001736838,0.0001243938,0.0001940447,0.000126213,0.0000666003,0.00002378473,0.9951734,0.0008582575,0.003259665],"genre_scores_gemma":[0.0003063696,0.00007129392,0.0004292936,0.0001423096,0.00001176314,0.00006617636,0.9966915,0.0001266743,0.002154592],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1918699,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02391168075934938,"score_gpt":0.429510111890116,"score_spread":0.4055984311307666,"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."}}