{"id":"W4205362389","doi":"10.1109/msec.2020.2988374","title":"Table of Contents","year":2020,"lang":"en","type":"article","venue":"IEEE Security & Privacy","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Niagara","funders":"","keywords":"Table (database); Computer science; Database","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001234908,0.0008682524,0.001160985,0.004051524,0.001613488,0.006743792,0.001508676,0.0015216,0.724837],"category_scores_gemma":[0.01373844,0.000358815,0.0006142814,0.002918142,0.0004509808,0.00319406,0.001708866,0.002347745,0.6258479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00202927,"about_ca_system_score_gemma":0.003143864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002356836,"about_ca_topic_score_gemma":0.002404003,"domain_scores_codex":[0.9986448,0.0001452472,0.0001116645,0.0002125719,0.0007837932,0.0001019649],"domain_scores_gemma":[0.9898481,0.00156255,0.0004522047,0.000596566,0.006023376,0.001517298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000788398,0.000009269634,0.0000502512,0.0001165934,0.000001543569,0.00001257784,0.000009648257,0.00003384453,0.00008284792,0.0007370373,0.9729372,0.02600131],"study_design_scores_gemma":[0.000003030999,0.000007663008,0.0001539234,0.000143416,0.000001968626,0.00003127701,0.00001570826,0.00002617101,0.00004085283,0.0004654416,0.9991071,0.000003454848],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004551591,0.008362831,0.003500215,0.02533248,0.1269112,0.0007868776,0.02117894,0.0031135,0.8103588],"genre_scores_gemma":[0.002501731,0.008863968,0.001890602,0.01100611,0.03265011,0.0003910807,0.01443806,0.001447796,0.9268106],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.275163,"threshold_uncertainty_score":0.3924866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03422416541100035,"score_gpt":0.2451721108215227,"score_spread":0.2109479454105224,"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."}}