{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001189677,0.0008276181,0.001339419,0.001647982,0.0006523056,0.0009633578,0.002169397,0.001342809,0.005128938],"category_scores_gemma":[0.003487933,0.0005882232,0.001180857,0.002084987,0.0006595688,0.00266138,0.001562967,0.002304904,0.003294485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135123,"about_ca_system_score_gemma":0.001501409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009252745,"about_ca_topic_score_gemma":0.02788037,"domain_scores_codex":[0.9992085,0.0003037393,0.00003624937,0.0002120244,0.0001355957,0.0001039356],"domain_scores_gemma":[0.9981328,0.00113945,0.0000690992,0.0003064483,0.000280412,0.0000717536],"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":[0.0004071072,0.0003202435,0.001633755,0.0003140695,0.0002532173,0.0001662914,0.0002464565,0.1338554,0.00749327,0.06708543,0.08938178,0.6988431],"study_design_scores_gemma":[0.00002442279,0.00002494654,0.0001650787,0.00001862189,0.0000294581,0.00003565835,0.00002278029,0.956027,0.001712278,0.03771896,0.004210423,0.00001031141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01565561,0.002728525,0.9685961,0.000880611,0.0003803567,0.000105715,0.002019356,0.005875663,0.003758028],"genre_scores_gemma":[0.4716548,0.001987938,0.4789233,0.001103546,0.0008341636,0.0004936866,0.01440276,0.002108559,0.02849135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009252745,"threshold_uncertainty_score":0.01839781,"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."}}