{"id":"W2148437670","doi":"10.18653/v1/2023.acl-long","title":"Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","year":2023,"lang":"en","type":"paratext","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":354,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Yuhan; Atomic Energy of Canada Limited; Strong; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Volume (thermodynamics); Computational linguistics; Association (psychology); Computer science; Linguistics; Natural language processing; Philosophy; Epistemology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01348262,0.001221272,0.002959837,0.006347352,0.003050588,0.01380765,0.00296286,0.00372875,0.2823546],"category_scores_gemma":[0.03631999,0.001161274,0.001242633,0.005593422,0.002193909,0.01145045,0.004110031,0.00509961,0.2549989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002949964,"about_ca_system_score_gemma":0.005826019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003973036,"about_ca_topic_score_gemma":0.005693414,"domain_scores_codex":[0.9941081,0.001849118,0.0008966652,0.001095331,0.00167685,0.0003740142],"domain_scores_gemma":[0.9631881,0.01536989,0.001573477,0.004025263,0.01213831,0.003705022],"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":[0.00004659424,0.00003652028,0.0004200318,0.0003754203,0.00002688382,0.00005394563,0.0001203633,0.00002353934,0.0002784349,0.0009880605,0.9481,0.0495302],"study_design_scores_gemma":[0.00001479144,0.00001544828,0.0009237775,0.0005585575,0.00001869274,0.0001212055,0.0002110529,0.000119818,0.00009661205,0.001756597,0.9961444,0.00001899219],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.007413968,0.162805,0.03068904,0.1800059,0.3446141,0.001026124,0.02787642,0.007619131,0.2379504],"genre_scores_gemma":[0.02069371,0.0912893,0.0331985,0.03931727,0.06544188,0.001714496,0.04735066,0.008260616,0.6927336],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2823546,"threshold_uncertainty_score":0.9445702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01096066040400236,"score_gpt":0.2699824330741872,"score_spread":0.2590217726701849,"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."}}