{"id":"W2375596347","doi":"","title":"Selection of Arbitrator in the United Protection of Database Security","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Access Control and Trust","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Selection (genetic algorithm); Database; Computer security; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007161073,0.00004018764,0.00006577976,0.000124074,0.0001343078,0.0000118769,0.0001996766,0.00004134293,0.000009953211],"category_scores_gemma":[0.000002455594,0.00003335334,0.00002496674,0.001033772,0.00008880889,0.00008124327,0.0000155237,0.00009905355,0.000002650814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002341824,"about_ca_system_score_gemma":0.00004335403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003856744,"about_ca_topic_score_gemma":0.003108605,"domain_scores_codex":[0.9994246,0.00007221625,0.0001864936,0.00009645421,0.0001161471,0.0001041335],"domain_scores_gemma":[0.9996053,0.00007312124,0.000101096,0.00009583052,0.0001059117,0.0000187281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001327781,0.002562667,0.04488881,0.0002287765,0.00007983077,0.000001610634,0.04682596,0.0000949409,0.1472589,0.5608692,0.001077503,0.1959791],"study_design_scores_gemma":[0.001350415,0.0000889887,0.09802388,0.00005407511,0.00005542128,0.000005730609,0.004899956,0.001643366,0.05269105,0.01302677,0.827831,0.0003293538],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4452853,0.00002800988,0.5494596,0.0005659582,0.00001207212,0.001483152,0.00001448802,0.00003346852,0.003117967],"genre_scores_gemma":[0.9962796,0.000005489853,0.003412887,0.00008383173,0.0001010139,0.00009655307,0.00001169125,0.000002411479,0.000006494716],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8267535,"threshold_uncertainty_score":0.5830269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01995173723771624,"score_gpt":0.3075439843837132,"score_spread":0.287592247145997,"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."}}