{"id":"W4248402989","doi":"10.1515/iupac.80.0213","title":"Cluster of Differentiation (CD) Nomenclature","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Heavy Metal Exposure and Toxicity","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Lymphocyte; Cadmium; Immunology; Beryllium; Chemistry; Biology; Computational biology","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":[0.001537173,0.002058174,0.002338724,0.008109429,0.001333749,0.003136448,0.003813034,0.001611639,0.07103692],"category_scores_gemma":[0.01340672,0.0004832632,0.001801361,0.01334937,0.0005870929,0.001598103,0.002414097,0.002205105,0.04882313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001554094,"about_ca_system_score_gemma":0.00470961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01577772,"about_ca_topic_score_gemma":0.02426746,"domain_scores_codex":[0.9972093,0.000362783,0.000632373,0.001054761,0.0004000497,0.0003407403],"domain_scores_gemma":[0.9961944,0.001224448,0.0005850772,0.0007131561,0.001011613,0.0002713549],"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":[0.0002657852,0.00003185925,0.008618197,0.003528036,0.0001704508,0.00009292189,0.0000637449,0.0005224253,0.0002407178,0.001617837,0.9717417,0.01310638],"study_design_scores_gemma":[0.0002626507,0.00004580184,0.01608999,0.001181092,0.0001740579,0.0003061245,0.0001867925,0.0006856168,0.0003525769,0.006025513,0.974637,0.00005276814],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004087095,0.0004449725,0.0002905474,0.0001231945,0.00007826035,0.00006165139,0.997276,0.0002635404,0.001053074],"genre_scores_gemma":[0.002049589,0.0006251712,0.001561362,0.0001528686,0.00003969524,0.0005849344,0.993771,0.0001420609,0.001073333],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07103692,"threshold_uncertainty_score":0.2376422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009135772873621386,"score_gpt":0.3416534475374036,"score_spread":0.3325176746637822,"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."}}