{"id":"W4385078273","doi":"10.18280/isi.280317","title":"A Distributed Densely Connected Convolutional Network Approach for Enhanced Recognition of Health-Related Topics: A Societal Analysis Case Study","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Social network analysis; Convolutional neural network; Computer network; Artificial intelligence; World Wide Web; Social media","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009381065,0.0001355603,0.0003358237,0.0003900319,0.0003991549,0.000144603,0.0002748931,0.0001099614,0.000005837829],"category_scores_gemma":[0.0002634503,0.0001344813,0.0001452368,0.003268231,0.00009384331,0.001317307,0.00009547344,0.00008593439,0.0000107746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001795818,"about_ca_system_score_gemma":0.0001137627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009818424,"about_ca_topic_score_gemma":0.0000145466,"domain_scores_codex":[0.9981973,0.0001148643,0.000967936,0.0001980822,0.000231589,0.0002901838],"domain_scores_gemma":[0.9983016,0.0001455235,0.0007500391,0.0003034614,0.0004586857,0.00004070255],"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":[0.0001716136,0.0008847178,0.01140708,0.001282732,0.004409059,0.00002773698,0.08303405,0.05409305,0.0002807621,0.05525241,0.007319096,0.7818377],"study_design_scores_gemma":[0.002362257,0.0006937397,0.02487816,0.0000530757,0.0002330483,0.0001017631,0.03433102,0.9121404,0.0006031047,0.0238951,0.0001994892,0.0005088175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3295843,0.00002933675,0.6687853,0.000101014,0.00008623738,0.0007168606,0.00006353497,0.0005676693,0.00006575699],"genre_scores_gemma":[0.9827602,0.000007012568,0.01529731,0.00002538,0.00001391445,0.000353941,0.001517816,0.000004075584,0.00002036901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8580474,"threshold_uncertainty_score":0.5483988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04156405975634932,"score_gpt":0.2769928398837452,"score_spread":0.2354287801273958,"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."}}