{"id":"W4243655971","doi":"10.1515/iupac.79.1531","title":"Laxative","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Historical and Linguistic Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Biology; Philosophy; 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":[],"consensus_categories":[],"category_scores_codex":[0.001976356,0.002050953,0.001395011,0.005066078,0.001383832,0.004169312,0.002688797,0.001709256,0.1779233],"category_scores_gemma":[0.01582416,0.0007561031,0.002271227,0.007135181,0.0005662652,0.003598048,0.002841369,0.001995955,0.2280187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001690142,"about_ca_system_score_gemma":0.003391728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01465031,"about_ca_topic_score_gemma":0.02941591,"domain_scores_codex":[0.9968823,0.0005622458,0.0006457951,0.0009150518,0.0006278422,0.0003668736],"domain_scores_gemma":[0.9934251,0.001799539,0.0006470609,0.0021051,0.001700292,0.0003228762],"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":[0.0001320827,0.00002185599,0.001389964,0.0009832386,0.00003273965,0.00002255799,0.00004270022,0.000161186,0.00009262482,0.001275249,0.9881477,0.007698075],"study_design_scores_gemma":[0.0001073563,0.00001367579,0.00225614,0.0004037464,0.0000230111,0.0000514935,0.0001177084,0.0001664174,0.0001630195,0.001630866,0.9950457,0.00002105144],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002497858,0.000175754,0.0002008142,0.0001098148,0.00008099458,0.00003968604,0.9950807,0.0006175226,0.003444864],"genre_scores_gemma":[0.0007480921,0.0001757167,0.0006591296,0.0002082502,0.00002447348,0.0001974686,0.9954399,0.0001989221,0.002348041],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1779233,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02579636166170634,"score_gpt":0.4584118217885478,"score_spread":0.4326154601268414,"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."}}