{"id":"W2906877930","doi":"10.4000/books.aaccademia.4868","title":"ITAmoji 2018: Emoji Prediction via Tree Echo State Networks","year":2018,"lang":"en","type":"book-chapter","venue":"Accademia University Press eBooks","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada; Università degli Studi di Napoli Federico II","keywords":"Emoji; Computer science; Parsing; Exploit; Artificial intelligence; Echo (communications protocol); Natural language processing; Tree (set theory); Word (group theory); State (computer science); Speech recognition; Linguistics; Algorithm; Mathematics; Social media; World Wide Web","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002974614,0.0006404702,0.0005665604,0.0002531849,0.0005727487,0.0002066337,0.002914394,0.001040223,0.00002592171],"category_scores_gemma":[0.00000584579,0.0006695382,0.000332782,0.00004548191,0.0002705245,0.000528621,0.002651564,0.001779347,0.0000391493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002584717,"about_ca_system_score_gemma":0.0001014524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008285663,"about_ca_topic_score_gemma":0.00002369434,"domain_scores_codex":[0.9968967,0.0001058252,0.0004489408,0.001219414,0.0005658272,0.0007632606],"domain_scores_gemma":[0.9974117,0.0001777693,0.0005724906,0.001259401,0.0002125347,0.000366087],"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":[0.0004114433,0.00007885593,0.00009520027,0.000272634,0.001511757,0.001751396,0.002082268,0.02479506,0.0001413154,0.208451,0.422102,0.3383071],"study_design_scores_gemma":[0.0006086914,0.0001768441,0.00004602087,0.0003354528,0.0001045662,0.00004192508,0.000005512671,0.2266315,0.00007545617,0.003617356,0.7675736,0.0007831046],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001050713,0.0002978285,0.2913252,0.00007588087,0.001750713,0.0005575609,0.00002793357,0.0007630376,0.7050968],"genre_scores_gemma":[0.004348482,0.0005236379,0.00230618,0.0002581888,0.001491325,0.000001039,0.00003019647,0.00008378128,0.9909571],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3454716,"threshold_uncertainty_score":0.9995756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01918379535388421,"score_gpt":0.1930641995621689,"score_spread":0.1738804042082847,"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."}}