{"id":"W4250368714","doi":"10.1109/msec.2020.2975335","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); Information retrieval; 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":[],"category_scores_codex":[0.0008013693,0.0008001137,0.0008613097,0.003444092,0.001979879,0.005146533,0.001530567,0.001530126,0.7820444],"category_scores_gemma":[0.008117457,0.0003329488,0.0005762291,0.003579985,0.0004698988,0.003136514,0.001844226,0.001692433,0.6928869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00243123,"about_ca_system_score_gemma":0.003318924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005209727,"about_ca_topic_score_gemma":0.005326528,"domain_scores_codex":[0.999132,0.00009667419,0.00005193086,0.0001444891,0.0004881256,0.00008687522],"domain_scores_gemma":[0.9956012,0.0006476071,0.0001760898,0.00041678,0.002554698,0.0006036158],"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":[0.00001127089,0.0000185765,0.0001335265,0.0001322294,0.000002012705,0.00002310335,0.00002178789,0.0000673301,0.0001157443,0.003301128,0.9550757,0.04109761],"study_design_scores_gemma":[0.000002412726,0.000007821073,0.0002449074,0.0001224333,0.000001571487,0.00004025024,0.00003106983,0.0000359793,0.00005435812,0.000999992,0.9984555,0.000003655497],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004579625,0.003928112,0.002091984,0.007744345,0.01145301,0.0004105233,0.01723913,0.001401709,0.9552732],"genre_scores_gemma":[0.003213909,0.004611603,0.001457489,0.004310999,0.003634923,0.0002167716,0.01466316,0.0006394228,0.9672518],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7820444,"threshold_uncertainty_score":0.3108873,"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."}}