{"id":"W2899374547","doi":"10.1002/nem.2049","title":"User identification via neural network based language models","year":2018,"lang":"en","type":"article","venue":"International Journal of Network Management","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Public Safety Canada; Defence Research and Development Canada","keywords":"Computer science; Identification (biology); Phishing; Artificial neural network; Language model; Artificial intelligence; Machine learning; ALARM; Natural language processing; Computer security; World Wide Web; The Internet","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":[0.0007401148,0.0001008688,0.0001043637,0.0001454781,0.00009320626,0.0003098184,0.001233058,0.00003295062,0.00003548253],"category_scores_gemma":[0.000007867687,0.00009350105,0.0001032599,0.000283694,0.00002765634,0.0007685165,0.0001753829,0.0001235862,0.00003279991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009115263,"about_ca_system_score_gemma":0.00001370859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009805544,"about_ca_topic_score_gemma":0.00001124177,"domain_scores_codex":[0.998503,0.00007604741,0.0004147953,0.0001738913,0.0006384674,0.0001938533],"domain_scores_gemma":[0.9988772,0.00004377826,0.0004071172,0.0002542713,0.0003566657,0.00006092398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001115957,0.00008161321,0.000489655,0.000006368925,0.0002720797,0.0001517697,0.000286498,0.7445291,0.0001074816,0.02514686,0.04299781,0.1858192],"study_design_scores_gemma":[0.0005077316,0.0001156773,0.004999083,0.00007088795,0.00002623355,0.00004994515,0.00001661027,0.9642793,0.0001419745,0.01715692,0.01250048,0.0001351744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01036984,0.0001402119,0.9792033,0.001396651,0.006946434,0.00008348003,4.368545e-7,0.0000462195,0.001813457],"genre_scores_gemma":[0.9627678,0.00002024096,0.03183841,0.001263904,0.003791738,0.000003492256,0.000002722331,0.000009129924,0.0003025098],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.952398,"threshold_uncertainty_score":0.3812862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135949337805106,"score_gpt":0.2589805654666247,"score_spread":0.2453856316861141,"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."}}