{"id":"W4237082696","doi":"10.1515/iupac.79.0976","title":"Carrier Protein","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","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":[0.001055797,0.002167301,0.00205065,0.003865199,0.001303409,0.003319327,0.002645269,0.002477304,0.08672784],"category_scores_gemma":[0.006233504,0.0006872722,0.001884567,0.006597421,0.0003942641,0.002007307,0.001712625,0.002100145,0.1300209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001740423,"about_ca_system_score_gemma":0.003433839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0200288,"about_ca_topic_score_gemma":0.03085543,"domain_scores_codex":[0.9987113,0.0001628809,0.00019931,0.0005014736,0.0002750187,0.0001500381],"domain_scores_gemma":[0.9983246,0.000482409,0.0002198469,0.000398752,0.0004137884,0.0001606469],"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":[0.0002980998,0.00003867034,0.001616106,0.00215364,0.0000866198,0.00005008032,0.00002874135,0.0003175872,0.0005035851,0.000738532,0.9867551,0.007413267],"study_design_scores_gemma":[0.0003223328,0.00003862561,0.005329459,0.0006540312,0.0001147383,0.0001792089,0.00005939685,0.0004366169,0.0006216159,0.00169602,0.9905054,0.00004262711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001792814,0.0003756677,0.00009195064,0.00008656577,0.00003159948,0.00001685016,0.9980693,0.000224737,0.0009240856],"genre_scores_gemma":[0.0003542327,0.000217164,0.0002623325,0.00009388036,0.000007014968,0.00006323896,0.9982722,0.00004220106,0.0006877876],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08672784,"threshold_uncertainty_score":0.2901335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01171746815997183,"score_gpt":0.3737570802735982,"score_spread":0.3620396121136264,"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."}}