{"id":"W4247691471","doi":"10.1109/msp.2016.1","title":"Table of Contents","year":2016,"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; Information retrieval; 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":[0.0007828071,0.001039871,0.00100773,0.00553226,0.001604059,0.004638492,0.001497364,0.001095604,0.8794783],"category_scores_gemma":[0.01092854,0.0003451122,0.0005646454,0.003977114,0.0003892894,0.002256184,0.00176278,0.001193694,0.8436944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00191272,"about_ca_system_score_gemma":0.003191594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005136255,"about_ca_topic_score_gemma":0.006684471,"domain_scores_codex":[0.9992586,0.00009434857,0.00003829466,0.0001174599,0.0004262268,0.0000651593],"domain_scores_gemma":[0.9949853,0.001054308,0.0002158217,0.0005192118,0.002577011,0.0006483226],"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":[0.0000125125,0.00002335152,0.0001030804,0.000123087,0.00000269626,0.00001202791,0.000008623772,0.00009362914,0.0000888662,0.001187626,0.9623934,0.03595116],"study_design_scores_gemma":[0.000006426146,0.00001142102,0.0002915219,0.0001935383,0.000003991504,0.00002573053,0.00002405879,0.00008131815,0.0001147974,0.001566155,0.9976745,0.000006534356],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004602328,0.002834193,0.003605439,0.003594859,0.008503268,0.0007542575,0.07658817,0.002877505,0.9007821],"genre_scores_gemma":[0.002344351,0.002974579,0.002210017,0.002815941,0.002609631,0.0006403436,0.05209902,0.00153529,0.9327708],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8794783,"threshold_uncertainty_score":0.1719096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05009947635031944,"score_gpt":0.2211526899978691,"score_spread":0.1710532136475496,"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."}}