{"id":"W4240558335","doi":"10.1515/iupac.81.0043","title":"Age Composition","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Aging and Gerontology Research","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Environmental risk assessment; Computer science; Ecology; Risk assessment; Biology; Data mining; Linguistics; Philosophy","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":[0.0009742624,0.001530791,0.001319338,0.003648026,0.000831945,0.002217719,0.00200647,0.001115756,0.078821],"category_scores_gemma":[0.007771037,0.0004509413,0.001431371,0.005619922,0.0002649255,0.001968502,0.001970536,0.001567596,0.1261005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124137,"about_ca_system_score_gemma":0.001739771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02307561,"about_ca_topic_score_gemma":0.04459596,"domain_scores_codex":[0.9987656,0.0001750467,0.0002106418,0.0004311692,0.0002343052,0.0001833108],"domain_scores_gemma":[0.9975315,0.0004221915,0.0003339437,0.0005874736,0.000910228,0.0002147113],"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":[0.0001391417,0.00002951364,0.006692506,0.0006712049,0.00005214411,0.0000372167,0.00005697917,0.0001465942,0.0001291676,0.0009682302,0.981806,0.009271338],"study_design_scores_gemma":[0.00008526388,0.00001355894,0.01548645,0.0003622457,0.00003876959,0.0001381672,0.0001881852,0.0002285683,0.000202486,0.001311867,0.9819207,0.00002372697],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006624946,0.0002392368,0.0001481231,0.0001134586,0.00006266151,0.00002249775,0.9962932,0.0002056052,0.002252699],"genre_scores_gemma":[0.001245123,0.0001858028,0.0003786573,0.0001071099,0.00001964964,0.00009707193,0.9953243,0.00006014041,0.002582116],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.078821,"threshold_uncertainty_score":0.2636825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03717623906251358,"score_gpt":0.5021007268692295,"score_spread":0.4649244878067159,"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."}}