{"id":"W4246757455","doi":"10.1515/iupac.79.1244","title":"Estimated Daily Intake (EDI)","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":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; Toxicology; Library science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002463477,0.0007133734,0.0007454414,0.00008485679,0.0002195029,0.00005081078,0.0009131536,0.0007546736,0.04993589],"category_scores_gemma":[0.0006663557,0.0006089433,0.0002047315,0.0001193252,0.0002672036,0.0001194697,0.0002159173,0.0009510366,0.00001216399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109962,"about_ca_system_score_gemma":0.0007443189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001191691,"about_ca_topic_score_gemma":0.00002728078,"domain_scores_codex":[0.9966102,0.0000170546,0.0006954352,0.0008411009,0.001140917,0.0006953239],"domain_scores_gemma":[0.9973312,0.00009452825,0.0004594576,0.001506257,0.0003236604,0.0002848975],"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":[0.000188007,0.0002906011,0.000003927134,0.0005918546,0.0001173481,0.0002073597,0.000008458876,0.000001873095,0.00446723,0.000002437827,0.9886302,0.005490694],"study_design_scores_gemma":[0.001206729,0.00004095145,5.81871e-7,0.001395296,0.0001377846,0.00002908698,0.00001972279,0.000002672801,0.005023269,0.0001059406,0.9912993,0.000738654],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001811736,0.0009942786,0.00007053289,0.0001443355,0.0008069826,0.00006990445,0.9955494,0.0002107105,0.001972645],"genre_scores_gemma":[0.00003580204,0.0007008255,0.0001361282,0.0002352772,0.001663808,0.00001697891,0.9891869,0.00006306385,0.007961217],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04992373,"threshold_uncertainty_score":0.9996362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01994471092096186,"score_gpt":0.3971011698727909,"score_spread":0.377156458951829,"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."}}