{"id":"W3179438688","doi":"10.1109/access.2021.3095967","title":"Authorship Classification in a Resource Constraint Language Using Convolutional Neural Networks","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Authorship Attribution and Profiling","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Athabasca University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Word2vec; Artificial intelligence; Convolutional neural network; Embedding; Classifier (UML); Hyperparameter; Natural language processing; Pattern recognition (psychology); Document classification; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005875365,0.0007675612,0.0003819389,0.001297009,0.000425336,0.001061189,0.0007357853,0.0005681217,0.001441185],"category_scores_gemma":[0.001898728,0.0001725637,0.0004960137,0.001113769,0.0003786301,0.002076214,0.000863201,0.0008172106,0.0009714915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001121081,"about_ca_system_score_gemma":0.0005582445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009220676,"about_ca_topic_score_gemma":0.01558007,"domain_scores_codex":[0.9994924,0.000118006,0.00004241086,0.0001522196,0.00009923764,0.00009568907],"domain_scores_gemma":[0.9992009,0.0003103054,0.0001137059,0.0001445462,0.0001848791,0.00004569965],"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":[0.001023334,0.0005472793,0.03103863,0.0003669886,0.0001678587,0.0008824022,0.0006740295,0.07825371,0.04517948,0.003657735,0.01657393,0.8216347],"study_design_scores_gemma":[0.00002191554,0.0001202024,0.01161794,0.00004236067,0.00003987956,0.0001797442,0.0004030312,0.9547108,0.02302648,0.003361163,0.006445426,0.00003102123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9087998,0.001175954,0.07497898,0.0006049458,0.0002149163,0.0001376368,0.002384119,0.003365523,0.008338202],"genre_scores_gemma":[0.9599831,0.0003050371,0.02738873,0.0001017836,0.00005275142,0.00006174388,0.004755624,0.00006867378,0.007282419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009220676,"threshold_uncertainty_score":0.01833403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1227674961873143,"score_gpt":0.3669254085632319,"score_spread":0.2441579123759176,"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."}}