{"id":"W4229978788","doi":"10.1515/iupac.79.1144","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 Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Multidisciplinary approach; Toxicology; Chemistry; Philosophy; Biology; Political science; Linguistics; Law; Organic chemistry","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":[0.00240917,0.002127246,0.001704385,0.004024663,0.001357583,0.005450345,0.00410625,0.002160351,0.2036487],"category_scores_gemma":[0.01844681,0.0007667022,0.002826203,0.007252024,0.0005101862,0.004453288,0.003235915,0.00255932,0.2997856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001759913,"about_ca_system_score_gemma":0.00363788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02452747,"about_ca_topic_score_gemma":0.04138215,"domain_scores_codex":[0.9970232,0.0005651914,0.0004520412,0.001090077,0.0005527993,0.0003167907],"domain_scores_gemma":[0.9942728,0.001633669,0.0004177173,0.001827345,0.001493401,0.0003550471],"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":[0.0000965486,0.00001763853,0.0009742004,0.0007128293,0.00004476399,0.00001467165,0.00003921292,0.0002432712,0.00005036859,0.001340593,0.9871301,0.009335741],"study_design_scores_gemma":[0.0001262303,0.00001412513,0.001468675,0.0003490913,0.00003196592,0.00003937579,0.00009232303,0.0004001897,0.0001320202,0.002849896,0.9944702,0.00002577527],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001754308,0.0001725671,0.0003027145,0.000272211,0.00009367103,0.00004412553,0.9936336,0.001523304,0.003782289],"genre_scores_gemma":[0.0006997148,0.0001864678,0.001092893,0.0002287511,0.00002798314,0.0002085333,0.9932239,0.0004316676,0.003900192],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2036487,"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."}}