{"id":"W4239604671","doi":"10.1515/iupac.87.0018","title":"Adenosine Receptor","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Inflammatory mediators and NSAID effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Psychology; Neuroscience; Chemistry; Linguistics; Data mining; Philosophy; 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":[0.0008075639,0.00130811,0.001516115,0.002404032,0.0006825562,0.002279872,0.001852249,0.001646409,0.07854135],"category_scores_gemma":[0.006074441,0.0005126332,0.001720188,0.004213449,0.0002451457,0.00130457,0.001272039,0.00179011,0.08724838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001054129,"about_ca_system_score_gemma":0.002374667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01237286,"about_ca_topic_score_gemma":0.02511125,"domain_scores_codex":[0.9988878,0.0001525382,0.0002601564,0.0003573003,0.0002081297,0.0001340461],"domain_scores_gemma":[0.9978405,0.0005886155,0.0003893189,0.0004685741,0.0005480575,0.0001649795],"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":[0.0003951023,0.00003334161,0.002993208,0.00328875,0.0001166828,0.00007281587,0.00002724501,0.0003248548,0.0003231448,0.0007606185,0.9788026,0.01286162],"study_design_scores_gemma":[0.0003724179,0.00004657083,0.01119995,0.001299078,0.0001599539,0.0003137737,0.00005754142,0.0003132397,0.0004382733,0.001699596,0.9840578,0.00004170054],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002390044,0.0004647587,0.0001078462,0.0001040283,0.0000435702,0.00002360745,0.9970742,0.0001521685,0.001790884],"genre_scores_gemma":[0.0008141016,0.0004140741,0.0003913043,0.0001703873,0.00001891581,0.0001136634,0.9967765,0.00003621426,0.00126485],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07854135,"threshold_uncertainty_score":0.2627469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01101239962504534,"score_gpt":0.3868724255279812,"score_spread":0.3758600259029359,"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."}}