{"id":"W4238176747","doi":"10.1515/iupac.87.0078","title":"Ataxia","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Animal testing and alternatives","field":"Veterinary","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Relation (database); Computer science; Psychology; Linguistics; Philosophy; Data mining","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":[0.0003627728,0.000458175,0.0005436126,0.0001463844,0.000128545,0.00005974193,0.0005982015,0.000254193,0.006369402],"category_scores_gemma":[0.0008137663,0.0003285099,0.0001756592,0.000104419,0.0001687417,0.00009335026,0.0003031199,0.0004960839,0.00003556645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002289261,"about_ca_system_score_gemma":0.0003046396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001802871,"about_ca_topic_score_gemma":0.00008228469,"domain_scores_codex":[0.9976309,0.0001083969,0.0004083964,0.0005938214,0.0008150945,0.0004433954],"domain_scores_gemma":[0.9982839,0.0001920797,0.0003051072,0.0007784597,0.000285776,0.000154636],"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":[0.0004177143,0.0001246309,0.00001616521,0.0001018264,0.00009306416,0.0006071973,0.000007624101,6.078022e-8,0.00004354037,0.000009209775,0.9953791,0.003199821],"study_design_scores_gemma":[0.000517206,0.001168806,0.00008204891,0.0006822203,0.00006055205,0.0001233159,0.00001444151,0.000003214411,0.000006412564,0.000205601,0.996679,0.0004571625],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008384705,0.0006906263,0.00008588649,0.000187004,0.0006587059,0.0001533442,0.9968973,0.0001939045,0.0002947127],"genre_scores_gemma":[0.0001970883,0.0003201488,0.0001143312,0.0001859584,0.002092017,0.00001051406,0.9950492,0.00005621835,0.00197452],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006333836,"threshold_uncertainty_score":0.9999167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09854943777634145,"score_gpt":0.5032612394181664,"score_spread":0.4047118016418249,"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."}}