{"id":"W3153176497","doi":"","title":"Standards for Evaluating Source Reliability and Information Credibility in Intelligence Production","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Canada; Defence Research and Development Canada","funders":"","keywords":"Credibility; Exploit; Quality (philosophy); Reliability (semiconductor); Variety (cybernetics); Computer science; Intelligence analysis; Context (archaeology); Information quality; Process (computing); Knowledge management; Production (economics); Risk analysis (engineering); Data science; Management science; Business; Information system; Engineering; Computer security; Political science","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.514056,0.00160596,0.003165719,0.03942818,0.008232146,0.02538835,0.007700324,0.008791271,0.003643147],"category_scores_gemma":[0.7429861,0.002049799,0.003571171,0.0280772,0.01977544,0.02421618,0.01315594,0.01120354,0.001674077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01639752,"about_ca_system_score_gemma":0.03065351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01424381,"about_ca_topic_score_gemma":0.01314229,"domain_scores_codex":[0.3853028,0.3277746,0.09102833,0.00953901,0.1822343,0.004120902],"domain_scores_gemma":[0.1248644,0.5588603,0.03963979,0.08224784,0.1923356,0.00205199],"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":[0.0003539858,0.0003090849,0.03174976,0.003851503,0.0004704458,0.0002347965,0.02412761,0.007658832,0.002193307,0.623011,0.0190987,0.286941],"study_design_scores_gemma":[0.0001998738,0.0007040611,0.05034487,0.02495412,0.000675628,0.0009959543,0.02680642,0.02233468,0.01396457,0.6697138,0.1883047,0.001001344],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03854757,0.01519314,0.7602159,0.02289396,0.001780233,0.007102701,0.002323146,0.001327005,0.1506164],"genre_scores_gemma":[0.2720872,0.005561716,0.7083818,0.002188155,0.0005259371,0.006258444,0.001284446,0.0005039795,0.003208312],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.514056,"threshold_uncertainty_score":0.5992554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01920542967810594,"score_gpt":0.3558897484925986,"score_spread":0.3366843188144927,"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."}}