{"id":"W2178204641","doi":"10.2469/cfm.v26.n6.20","title":"Building Up Infrastructure","year":2015,"lang":"en","type":"article","venue":"CFA Magazine","topic":"Water Governance and Infrastructure","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Novelis (Canada)","funders":"","keywords":"Critical infrastructure; Business; Computer science; Computer security","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":[],"consensus_categories":[],"category_scores_codex":[0.0002545055,0.0001053535,0.0001278549,0.00003858734,0.0001594281,0.00009249597,0.0002955622,0.0001127661,0.0004665547],"category_scores_gemma":[0.0002650836,0.00009076129,0.00004059157,0.0002532825,0.0001604475,0.0003945222,0.00006383658,0.00015788,0.0003053585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001232998,"about_ca_system_score_gemma":0.0001963361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001944867,"about_ca_topic_score_gemma":0.0001414423,"domain_scores_codex":[0.9989352,0.00004983473,0.0001282608,0.0001783105,0.0003807686,0.0003276325],"domain_scores_gemma":[0.9994025,0.00001471766,0.00006781136,0.000174065,0.0001220198,0.0002189502],"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":[0.0000264427,0.000009559253,0.01311004,0.000007982578,0.00001536731,0.00001751821,0.01172567,0.0001052545,0.001861133,0.09282447,0.8560466,0.02424997],"study_design_scores_gemma":[0.0003034144,0.00002059983,0.01316855,0.000009659529,0.000006073799,0.00000306235,0.000517667,0.00001639992,0.0003778894,0.0310125,0.9544331,0.0001311334],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6738209,0.0003692501,0.001465718,0.004219943,0.003972999,0.0002372048,0.0000191215,0.0002723093,0.3156226],"genre_scores_gemma":[0.9769847,0.00003616335,0.004343045,0.0007624933,0.001519125,0.000004466039,0.00000528313,0.00001623045,0.01632844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3031639,"threshold_uncertainty_score":0.5108447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02525173888113847,"score_gpt":0.3045876968159994,"score_spread":0.2793359579348609,"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."}}