{"id":"W3026511322","doi":"10.18280/ijsse.100216","title":"Entropy Weight-Based Matter-Element Extension Model for Security Evaluation and Prewarning Mechanism of National Defense Science and Technology","year":2020,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Advanced Decision-Making Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extension (predicate logic); Entropy (arrow of time); Computer science; Computer security; Mechanism (biology); National security; Reliability engineering; Systems engineering; Risk analysis (engineering); Engineering; Political science; Business; Thermodynamics; Physics; Programming language","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":[0.001208688,0.00009886944,0.0001633941,0.0003723302,0.00006821696,0.00005384729,0.0003573682,0.00004903052,0.00000168666],"category_scores_gemma":[0.0008641181,0.00009552146,0.00002755207,0.0001934202,0.00006583447,0.0005509414,0.0002348031,0.0001477529,8.160567e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001088048,"about_ca_system_score_gemma":0.0001537227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.179056e-7,"about_ca_topic_score_gemma":3.161993e-7,"domain_scores_codex":[0.99839,0.00001436062,0.0003833727,0.0002197115,0.0008824058,0.0001102122],"domain_scores_gemma":[0.9975955,0.0001606045,0.0002684112,0.00007359976,0.001825573,0.00007629133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003833026,0.0001115005,0.0003925827,0.0001321057,0.00009951154,0.00001803069,0.003879166,0.1060515,0.08143422,0.7851313,0.00007356343,0.02229313],"study_design_scores_gemma":[0.0005551714,0.00009593306,0.00009306064,0.000107407,0.00000739896,0.00005658745,0.00001554646,0.8788988,0.008940688,0.1110451,0.0001083561,0.00007599154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06173299,0.0002208616,0.9348841,0.002866205,0.0001039192,0.0001454892,0.00001203389,0.0000266867,0.000007664948],"genre_scores_gemma":[0.8331231,0.00006743368,0.1666414,0.0001271992,0.0000312353,0.00000358515,0.000001134413,0.000004656712,1.805882e-7],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7728472,"threshold_uncertainty_score":0.3895252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551426833807831,"score_gpt":0.2836746083946954,"score_spread":0.2681603400566172,"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."}}