{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0105476,0.001434388,0.001250962,0.008343361,0.00113735,0.006107213,0.004058761,0.003105052,0.003831064],"category_scores_gemma":[0.06413136,0.0008806087,0.001598055,0.003547027,0.002559663,0.007638124,0.006807819,0.003815936,0.001230122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001500216,"about_ca_system_score_gemma":0.001651887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001343078,"about_ca_topic_score_gemma":0.001681501,"domain_scores_codex":[0.9886108,0.006581163,0.0006597639,0.001822295,0.001978412,0.0003476354],"domain_scores_gemma":[0.9511378,0.03028277,0.004613786,0.007494764,0.005365197,0.001105494],"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":[0.0009290891,0.0006148062,0.01483372,0.001082066,0.0003073118,0.001189895,0.003944532,0.1328925,0.01619728,0.1511982,0.007015775,0.6697949],"study_design_scores_gemma":[0.00007600648,0.000176107,0.002198214,0.0002174851,0.00007906627,0.0005183289,0.0007262999,0.7566369,0.01118518,0.2163486,0.0117354,0.0001024155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008464939,0.0004254099,0.9869468,0.0006039563,0.0000554706,0.0002426904,0.0003596918,0.001023764,0.001877267],"genre_scores_gemma":[0.3344666,0.0003800414,0.661497,0.0002220532,0.0001177579,0.0003749224,0.0008663606,0.0001632658,0.001912044],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0105476,"threshold_uncertainty_score":0.05578172,"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."}}