{"id":"W2096736620","doi":"10.1080/02684520701798106","title":"Intelligence in fiction","year":2008,"lang":"en","type":"article","venue":"Intelligence & National Security","topic":"Intelligence, Security, War Strategy","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Covert; Nothing; Espionage; Agency (philosophy); Military intelligence; Officer; Headline; Law; Action (physics); Media studies; Political science; Sociology; Philosophy; Social science; Epistemology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001945751,0.0002881005,0.0002961546,0.000496258,0.0008046207,0.00009091223,0.0008906987,0.000347751,0.001461791],"category_scores_gemma":[0.001662937,0.0003307668,0.000164719,0.001811124,0.0008490689,0.0008287974,0.00009540314,0.0006991579,0.0008772544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008890131,"about_ca_system_score_gemma":0.001037908,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006847369,"about_ca_topic_score_gemma":0.008002155,"domain_scores_codex":[0.9955666,0.0003944773,0.0008067692,0.0006601674,0.001796588,0.0007754122],"domain_scores_gemma":[0.9978939,0.000476902,0.0001963169,0.0002516768,0.0009367795,0.0002444152],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004679524,0.0004297173,0.004878148,0.0000142332,0.00001520729,0.0000733949,0.02811628,0.001155847,0.00004376535,0.9579812,0.001601635,0.005643747],"study_design_scores_gemma":[0.000115539,0.0001671613,0.005486148,0.0001085383,0.00001112615,0.00008270298,0.01545464,0.007341291,0.008426943,0.8739278,0.08776084,0.001117218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2124397,0.001493286,0.02956884,0.002434432,0.002730256,0.00154076,0.00007348688,0.0005840127,0.7491353],"genre_scores_gemma":[0.9960184,0.001826621,0.0005354738,0.0003306312,0.0005544052,0.00006055324,0.00002126858,0.00002100501,0.000631702],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7835786,"threshold_uncertainty_score":0.9999145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05616693063213289,"score_gpt":0.3565386188334672,"score_spread":0.3003716882013343,"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."}}