{"id":"W4234016332","doi":"10.1515/iupac.78.0243","title":"Diffusion","year":2016,"lang":"fr","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Relation (database); Management science; Environmental chemistry; Data science; Chemistry; Engineering; Data mining; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001586101,0.001939171,0.00137124,0.005849744,0.001357237,0.004475005,0.003249732,0.002067477,0.1478781],"category_scores_gemma":[0.01588862,0.0007021557,0.002107616,0.01064205,0.0005024114,0.004156956,0.002752898,0.002504881,0.1716927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002385668,"about_ca_system_score_gemma":0.003611257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04688874,"about_ca_topic_score_gemma":0.075051,"domain_scores_codex":[0.9975776,0.0003970843,0.0004614428,0.0007777796,0.0005185048,0.0002676061],"domain_scores_gemma":[0.9944345,0.001724801,0.0006572584,0.001428853,0.001451825,0.0003028286],"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":[0.0000655432,0.00001403422,0.00116445,0.0007413145,0.00002916342,0.0000193039,0.00004861448,0.0001916302,0.00005849074,0.001434362,0.9911021,0.005130966],"study_design_scores_gemma":[0.00007632809,0.000008894782,0.002448221,0.000454456,0.00002013813,0.00004842066,0.0001105175,0.0002404356,0.000114657,0.0017614,0.9946901,0.00002649852],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001335652,0.0001183107,0.0001050707,0.0001377436,0.00003039942,0.0000171093,0.9973455,0.0003072327,0.001805063],"genre_scores_gemma":[0.0005051952,0.0001327349,0.0003857936,0.00009720175,0.00001129491,0.0001140385,0.9968361,0.0001238999,0.001793761],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8521218,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491157796993549,"score_gpt":0.403734606703148,"score_spread":0.3888230287332126,"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."}}