{"id":"W2906283054","doi":"10.3389/fpsyg.2018.02640","title":"Correcting Judgment Correctives in National Security Intelligence","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Intelligence, Security, War Strategy","field":"Social Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"Ministère de la Défense Nationale","keywords":"Psychology; Excellence; Set (abstract data type); Debiasing; Intelligence analysis; Interpretation (philosophy); Test (biology); Cognitive psychology; Social psychology; Best practice; Quality (philosophy); Epistemology; Political science; Computer science; Law","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001921425,0.0001560943,0.0002582301,0.0004927968,0.0002181767,0.00003801028,0.0004507398,0.000276354,0.0003788269],"category_scores_gemma":[0.0007227258,0.0001833227,0.00005114585,0.00107106,0.001112438,0.0002050861,0.00005172572,0.0004821598,0.0001199024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004545817,"about_ca_system_score_gemma":0.0002382154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001582676,"about_ca_topic_score_gemma":0.01301573,"domain_scores_codex":[0.9974762,0.0005424585,0.0004280226,0.0005410849,0.0003919854,0.0006202422],"domain_scores_gemma":[0.9992464,0.000148912,0.0001236966,0.0001767237,0.0002169311,0.0000873148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004181998,0.00076593,0.3866968,0.00001815434,0.00004867836,0.00008460921,0.1747231,0.00003327566,0.00004329449,0.1194821,0.07025505,0.2474308],"study_design_scores_gemma":[0.0003796148,0.0003199685,0.00991356,0.00007882043,0.000005074715,0.00002499631,0.05225059,0.001501803,0.0007426673,0.8931672,0.04110257,0.0005131494],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1592605,0.0009092325,0.0649856,0.001743927,0.03177041,0.0007970175,0.00001040724,0.0001329295,0.74039],"genre_scores_gemma":[0.9950076,0.000180993,0.003248146,0.000756432,0.0005548936,0.00003635785,0.000003054328,0.00001254878,0.0001999688],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8357471,"threshold_uncertainty_score":0.7475682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04042566321168534,"score_gpt":0.3936598100677,"score_spread":0.3532341468560146,"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."}}