{"id":"W3171978172","doi":"10.18653/v1/2021.naacl-main.333","title":"Inductive Topic Variational Graph Auto-Encoder for Text Classification","year":2021,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"China Scholarship Council","keywords":"Computer science; Autoencoder; Computational linguistics; Natural language processing; Artificial intelligence; Encoder; Graph; Linguistics; Theoretical computer science; Philosophy; Deep learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001144205,0.00005476635,0.00006392332,0.00004096188,0.00007898844,0.00008314272,0.0002274759,0.00004791133,0.00005921148],"category_scores_gemma":[0.00004609111,0.00005165714,0.00004175384,0.0001802376,0.000008492401,0.0003128135,0.00006692875,0.00005314187,0.00001574888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003290865,"about_ca_system_score_gemma":0.0001459708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001069665,"about_ca_topic_score_gemma":0.000008703662,"domain_scores_codex":[0.9992857,0.00002560101,0.0001352138,0.0002984726,0.0001392378,0.0001157849],"domain_scores_gemma":[0.9993448,0.00008297773,0.00003723747,0.0003094627,0.0001935173,0.00003199705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[4.696533e-7,0.00002258432,0.0003087009,0.000003311219,0.000008395243,5.103434e-7,0.0002621915,0.0001472891,0.001419006,0.9755624,0.0003907148,0.02187443],"study_design_scores_gemma":[0.0002366564,0.00001275397,0.01687185,0.000004035297,0.000004099627,0.000004957257,0.0000743058,0.78079,0.001406257,0.1952181,0.005262883,0.0001141014],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002042833,0.00001884395,0.9847952,0.006543377,0.0004170044,0.00009718478,0.000001027281,0.00008063722,0.006003938],"genre_scores_gemma":[0.4310074,0.00000171171,0.5656307,0.0005985795,0.0001202477,0.00003849475,0.000005848868,0.0000031112,0.00259399],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7806427,"threshold_uncertainty_score":0.2106517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06204689173918598,"score_gpt":0.2811516705133185,"score_spread":0.2191047787741325,"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."}}