{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001028201,0.001705921,0.001821311,0.002876887,0.000642058,0.002786173,0.002522213,0.001672761,0.07552037],"category_scores_gemma":[0.007801964,0.0004651341,0.00209417,0.003896643,0.0003134936,0.001628612,0.001838654,0.001351978,0.08408351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001218789,"about_ca_system_score_gemma":0.002772881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0113527,"about_ca_topic_score_gemma":0.02501438,"domain_scores_codex":[0.9988493,0.0001740569,0.0002269015,0.0004092238,0.0002139555,0.0001265587],"domain_scores_gemma":[0.9976079,0.0006373347,0.0004255837,0.0005070727,0.0006241313,0.0001978791],"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":[0.0005343286,0.00004185042,0.004815482,0.004475345,0.0001989877,0.00008096413,0.00003636505,0.000523027,0.0003356454,0.0007631616,0.9643142,0.02388062],"study_design_scores_gemma":[0.0005112754,0.00005181754,0.008855714,0.001758575,0.0002278668,0.0003619093,0.00007927754,0.0005634907,0.0006016305,0.002277592,0.9846569,0.00005398392],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002625444,0.0006178647,0.0002022162,0.0000926877,0.00005484729,0.00003561005,0.9969541,0.0003591888,0.001420974],"genre_scores_gemma":[0.00112967,0.0004624538,0.0006965428,0.0002206756,0.00003095624,0.0001742926,0.996124,0.00006871147,0.00109276],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07552037,"threshold_uncertainty_score":0.2526408,"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."}}