{"id":"W4234038410","doi":"10.1515/iupac.79.2021","title":"Skeletal Fluorosis","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Fluoride Effects and Removal","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006866451,0.001509961,0.001481545,0.003087449,0.0005060833,0.001461459,0.001801365,0.001396704,0.06506279],"category_scores_gemma":[0.005989362,0.0004457643,0.001730758,0.004288802,0.0002443292,0.0009696785,0.001176378,0.001067316,0.04729466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001104685,"about_ca_system_score_gemma":0.002014033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02359642,"about_ca_topic_score_gemma":0.0517338,"domain_scores_codex":[0.9992031,0.00009964225,0.0001761258,0.0002784684,0.0001709295,0.0000716811],"domain_scores_gemma":[0.9978441,0.0005026644,0.0004736229,0.0003784364,0.0006714619,0.0001296573],"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":[0.0003802404,0.00003449227,0.007632835,0.004183919,0.0002033503,0.0000919978,0.00002715806,0.0004121574,0.0002576874,0.0005427881,0.9696801,0.01655327],"study_design_scores_gemma":[0.0005276414,0.00004981985,0.03401943,0.002584191,0.0002895229,0.0005125506,0.00009160127,0.0003979278,0.0005430165,0.001453,0.9594772,0.0000540711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002426969,0.0002520156,0.00006451824,0.00004147468,0.00001658965,0.00001484767,0.9983753,0.00008768089,0.0009048982],"genre_scores_gemma":[0.0009473161,0.0003129305,0.0003020827,0.00008162828,0.00001186332,0.00008607913,0.997169,0.00002444674,0.001064686],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06506279,"threshold_uncertainty_score":0.2176567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006349187861046395,"score_gpt":0.335450206319927,"score_spread":0.3291010184588806,"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."}}