{"id":"W2066783897","doi":"10.1145/2699910","title":"A Visualizable Evidence-Driven Approach for Authorship Attribution","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Information and System Security","topic":"Authorship Attribution and Profiling","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stylometry; Computer science; Authorship attribution; Context (archaeology); Identification (biology); Attribution; The Internet; Data science; Information retrieval; World Wide Web; Natural language processing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001748583,0.0001612432,0.0002047594,0.0002053154,0.0004246479,0.0003418422,0.0004328761,0.0001849517,0.000003704434],"category_scores_gemma":[0.0001709927,0.0001495321,0.00008742707,0.0004382213,0.00003025527,0.002880933,0.00001964547,0.0001956099,0.0000494502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001939499,"about_ca_system_score_gemma":0.0001348829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003171996,"about_ca_topic_score_gemma":0.000002637227,"domain_scores_codex":[0.9984832,0.0001966533,0.0004794727,0.0002208713,0.0003542414,0.0002654939],"domain_scores_gemma":[0.9985381,0.0001617761,0.0001821597,0.0004701126,0.0003752467,0.0002725393],"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":[0.0004364303,0.0002467674,0.000467691,0.001912679,0.0001134435,0.000001301153,0.03972296,0.01056269,0.00002910094,0.8981628,0.002059563,0.04628462],"study_design_scores_gemma":[0.001084608,0.000279772,0.00009446839,0.0001461769,0.00002664017,0.0000519191,0.002121,0.9821213,0.0008884027,0.002821016,0.01004858,0.0003160809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002414159,0.00007180223,0.9948112,0.0006885426,0.0004349641,0.0006839707,0.00004742468,0.0003911222,0.000456781],"genre_scores_gemma":[0.9641103,0.00001245033,0.03537202,0.0001831525,0.00003304584,0.0001861586,0.00005364829,0.000004782203,0.00004450315],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9715586,"threshold_uncertainty_score":0.6097744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1074829618696274,"score_gpt":0.3201323593290201,"score_spread":0.2126493974593927,"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."}}