{"id":"W6929345185","doi":"10.48448/9pdg-b496","title":"Segatron: Segment-Aware Transformer for Language Modeling and Understanding","year":2021,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Advanced Electron Microscopy Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Perplexity; Language model; Transformer; Security token; Sentence; Question answering; Encoding (memory)","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":[0.0009109544,0.003115298,0.0007422991,0.001687665,0.0005762535,0.001606089,0.002867434,0.001321676,0.02377349],"category_scores_gemma":[0.003272751,0.001140353,0.002312436,0.001143986,0.0005730698,0.004250629,0.002087711,0.002817391,0.01804878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001485062,"about_ca_system_score_gemma":0.002122347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01124595,"about_ca_topic_score_gemma":0.02719626,"domain_scores_codex":[0.9993548,0.0001249062,0.00004748865,0.0003060245,0.0001010746,0.00006574567],"domain_scores_gemma":[0.9991468,0.0003548157,0.00004436249,0.0002650915,0.0001382886,0.00005063293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007064634,0.000323602,0.003005608,0.001284799,0.0003342715,0.0005135588,0.0005010822,0.05707162,0.0267045,0.01829353,0.2780322,0.6132288],"study_design_scores_gemma":[0.0001266404,0.0001553683,0.0007174526,0.00006766748,0.00008757416,0.0004055765,0.0001711012,0.8723541,0.03134717,0.0267291,0.06775017,0.00008798434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01379132,0.0006598186,0.6459583,0.0004498761,0.0003002174,0.0003433846,0.02798188,0.303786,0.006729155],"genre_scores_gemma":[0.161126,0.0008468162,0.6542439,0.0006873025,0.0000937127,0.0009346917,0.1472329,0.01592097,0.01891371],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02377349,"threshold_uncertainty_score":0.07953024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02343247087210898,"score_gpt":0.3510913044773185,"score_spread":0.3276588336052095,"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."}}