{"id":"W4253375181","doi":"10.1515/iupac.78.0379","title":"in Vivo","year":2016,"lang":"en","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; Relation (database); Chemical nomenclature; Computer science; Data science; Management 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":[0.001596052,0.002467853,0.001954284,0.003224605,0.001355929,0.003885999,0.003295481,0.002652389,0.1611397],"category_scores_gemma":[0.009554719,0.0007476072,0.002163408,0.005090677,0.000528028,0.002930905,0.002597511,0.002219464,0.1516224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001935796,"about_ca_system_score_gemma":0.003205151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0198686,"about_ca_topic_score_gemma":0.04155518,"domain_scores_codex":[0.998024,0.0003145221,0.0003281807,0.0007036981,0.0004214804,0.0002081386],"domain_scores_gemma":[0.9957628,0.001227061,0.0006535582,0.001111981,0.0009979957,0.0002465791],"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":[0.0003281849,0.00003987814,0.001939107,0.002732237,0.00008239665,0.00005339868,0.00004289174,0.0002606426,0.0003902359,0.00127019,0.9852011,0.007659655],"study_design_scores_gemma":[0.0002077181,0.00003118575,0.003606038,0.001029836,0.0000869946,0.0001294296,0.00006837356,0.0001703283,0.0004074176,0.001960459,0.9922646,0.00003765015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001451416,0.0002931706,0.0001471645,0.000103045,0.00003450625,0.00002416421,0.9973904,0.0002508788,0.001611384],"genre_scores_gemma":[0.0004631572,0.0002602645,0.0004130682,0.0002268816,0.00001320365,0.0001371549,0.9970675,0.00008674608,0.001332112],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8388603,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01439929197589664,"score_gpt":0.4184332551955647,"score_spread":0.4040339632196681,"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."}}