{"id":"W4220846184","doi":"10.1109/msec.2021.3130864","title":"Table of Contents","year":2022,"lang":"en","type":"article","venue":"IEEE Security & Privacy","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004553982,0.00009189719,0.0003315197,0.0001293369,0.0002137464,0.00002442478,0.0004223875,0.00002225315,0.01248982],"category_scores_gemma":[0.00005055396,0.0001201573,0.0001085729,0.0002053137,0.00007838705,0.0001512345,0.0003296037,0.000117799,0.001830597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006792416,"about_ca_system_score_gemma":0.00001302523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003934075,"about_ca_topic_score_gemma":0.000004023297,"domain_scores_codex":[0.9989423,0.00001145828,0.0004313954,0.0003328629,0.00004435479,0.0002376826],"domain_scores_gemma":[0.9992732,0.00002372803,0.0002871275,0.0003469618,0.00002154744,0.00004740071],"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":[0.00005389263,0.0005246503,0.04398454,0.00005396164,0.0002459133,0.000008349216,0.009299857,0.0002501305,0.0001243792,0.1831446,0.7620081,0.0003016836],"study_design_scores_gemma":[0.000702522,0.0000557929,0.001319786,0.000003183881,0.000005759352,0.00000243352,0.0009371282,0.0004750764,0.0004251239,0.02741168,0.9684626,0.000198945],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6680135,0.001694073,0.0000809155,0.0003312891,0.005302256,0.0002376563,0.001759178,0.00004188715,0.3225393],"genre_scores_gemma":[0.9688501,0.00006538287,0.00005592902,0.000172821,0.00004112793,0.00002253371,0.000008389492,0.00000956119,0.03077412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3008367,"threshold_uncertainty_score":0.9989466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05032299267264739,"score_gpt":0.219518135951509,"score_spread":0.1691951432788616,"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."}}