{"id":"W2900229396","doi":"10.2139/ssrn.3215960","title":"Current Cyberthreats and Relevant Legal Instruments in EU and Canada","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Current (fluid); Political science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001213665,0.0001927293,0.0003958126,0.005986501,0.007312667,0.006821134,0.001983347,0.001947801,0.006718005],"category_scores_gemma":[0.009243418,0.0003093751,0.0004584031,0.01038163,0.004251641,0.001930055,0.002588568,0.002468866,0.0003112725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07792791,"about_ca_system_score_gemma":0.1080406,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941344,"about_ca_topic_score_gemma":0.9976302,"domain_scores_codex":[0.997523,0.0001102957,0.0001044516,0.0001633246,0.0007329989,0.00136593],"domain_scores_gemma":[0.9867343,0.00135339,0.002392875,0.0001846694,0.005299094,0.004035569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003195649,0.0002274329,0.9009789,0.0001668616,0.0001080191,0.0006710563,0.01695139,0.001040658,0.0001998847,0.02587903,0.01630563,0.0371516],"study_design_scores_gemma":[0.00001363264,0.00003700388,0.9161522,0.0003290173,0.00005776699,0.0001454858,0.0512588,0.0004800428,0.0001643024,0.001151096,0.03015148,0.00005934984],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609311,0.003565151,0.0001027709,0.006726762,0.00005554741,0.00003549269,0.002088575,0.00001244391,0.02648206],"genre_scores_gemma":[0.9918031,0.002146268,0.00006609995,0.0006188561,0.00001576983,0.0000077434,0.000572977,0.000008103198,0.004761244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07792791,"threshold_uncertainty_score":0.5654092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006508865440673097,"score_gpt":0.2298821668378905,"score_spread":0.2233733013972174,"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."}}