{"id":"W4232536564","doi":"10.1515/iupac.79.1898","title":"Receptor","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cell Adhesion Molecules Research","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; Biology; Philosophy; 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":[0.001614822,0.001865714,0.001548995,0.002823381,0.0009129808,0.003323322,0.003041394,0.001924064,0.1697927],"category_scores_gemma":[0.01227434,0.0005576983,0.00201477,0.004278119,0.0003958655,0.001988349,0.001790106,0.001742159,0.2281542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001541943,"about_ca_system_score_gemma":0.003033046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01490172,"about_ca_topic_score_gemma":0.02849874,"domain_scores_codex":[0.9976662,0.0004134024,0.0003388857,0.0008883065,0.0004425814,0.0002506801],"domain_scores_gemma":[0.9961917,0.00105579,0.0003569075,0.0009895233,0.001144308,0.0002617324],"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":[0.0001517839,0.00002372106,0.001503379,0.0009769207,0.00005275067,0.00002508116,0.0000212365,0.0002163551,0.00009424546,0.0007142964,0.9884587,0.007761445],"study_design_scores_gemma":[0.0002337965,0.00002822379,0.00311506,0.00053671,0.00006357141,0.00009010683,0.00008033597,0.0002999665,0.0002449524,0.001851183,0.9934276,0.00002852029],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001511641,0.0001635257,0.0001591614,0.0001196499,0.00005062106,0.00003584266,0.9970633,0.0003393055,0.001917399],"genre_scores_gemma":[0.0005003361,0.0001205453,0.0004226593,0.000199085,0.00001654707,0.0001767915,0.9967729,0.00007874413,0.001712432],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1697927,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02251122824949622,"score_gpt":0.4457168452131731,"score_spread":0.4232056169636769,"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."}}