{"id":"W4235103482","doi":"10.1515/iupac.79.1499","title":"Interstitial Fluid","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Medical Imaging and Pathology Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Organic chemistry","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":[0.0004754931,0.0003900109,0.0009337349,0.0002021319,0.00009390969,0.0000141339,0.0001991097,0.0003873358,0.004373848],"category_scores_gemma":[0.002072178,0.0002482799,0.0002149531,0.00009824725,0.0006227476,0.0000281502,0.0001840185,0.0007224291,0.00001508898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002223194,"about_ca_system_score_gemma":0.0006557333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004374077,"about_ca_topic_score_gemma":0.0000777619,"domain_scores_codex":[0.9976805,0.00007476277,0.0004352878,0.0004917569,0.0008809456,0.0004367174],"domain_scores_gemma":[0.9983561,0.0001310824,0.0001323808,0.0006898444,0.0003954899,0.0002951161],"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":[0.0003791527,0.0001822125,0.0000354367,0.0002595519,0.0002471921,0.001082341,0.000016061,1.157901e-8,0.00002135185,0.000002132552,0.9924248,0.005349718],"study_design_scores_gemma":[0.001863215,0.0005736118,0.00004821942,0.001488506,0.0004867931,0.0002992988,0.00002583018,0.000001316472,0.00001858483,0.00003641474,0.9949028,0.0002553496],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009047017,0.001898185,0.0002561558,0.006858801,0.001942281,0.0002262092,0.9883028,0.00009983098,0.0003252483],"genre_scores_gemma":[0.00002583218,0.002033288,0.00007997995,0.003093787,0.002897789,0.00001359904,0.989996,0.00003111751,0.001828647],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005094368,"threshold_uncertainty_score":0.999997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02369023318954207,"score_gpt":0.4453422849297858,"score_spread":0.4216520517402438,"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."}}