{"id":"W2908510269","doi":"10.4000/books.aaccademia.4577","title":"Fully Convolutional Networks for Text Classification","year":2018,"lang":"en","type":"preprint","venue":"Accademia University Press eBooks","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada; Università degli Studi di Napoli Federico II","keywords":"Emoji; Computer science; Task (project management); Convolutional neural network; Artificial intelligence; Machine learning; Data mining; World Wide Web; Social media; Engineering","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":[0.0003249848,0.000246424,0.0002529873,0.0001207051,0.0002754389,0.0001266771,0.002509677,0.0007966345,0.000003008736],"category_scores_gemma":[0.00003243563,0.0003011024,0.0001681184,0.00002696164,0.0001313218,0.0002108156,0.002417421,0.0007629349,0.000004208657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002878089,"about_ca_system_score_gemma":0.0003040931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009423866,"about_ca_topic_score_gemma":0.000004631477,"domain_scores_codex":[0.9981354,0.0001037898,0.0002389958,0.0008969909,0.00025547,0.0003693355],"domain_scores_gemma":[0.9980795,0.0001665539,0.0003166143,0.0009894141,0.0003152319,0.0001326539],"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":[0.00005637505,0.00002167622,0.0001114002,0.00009635997,0.0001172202,0.000005727256,0.0004688333,0.008184372,0.00006816741,0.9590239,0.01588192,0.01596407],"study_design_scores_gemma":[0.0003926476,0.00001984589,0.0003900809,0.00006653411,0.00004416738,0.000002672384,0.00001849602,0.8028845,0.00008826325,0.003328847,0.1924434,0.000320514],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001372657,0.00007469713,0.9681004,0.0002825343,0.001011126,0.0006357804,0.00002891995,0.0003028281,0.02819101],"genre_scores_gemma":[0.7156749,0.0001157377,0.22089,0.0006818689,0.002457452,0.0000451479,0.000166018,0.0000631415,0.05990574],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.955695,"threshold_uncertainty_score":0.9999441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0656289605154812,"score_gpt":0.2576380090301897,"score_spread":0.1920090485147085,"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."}}