{"id":"W3175732993","doi":"","title":"Systematic Monitoring of Forecasting Skill in Strategic Intelligence","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Strategic intelligence; Strategic planning; Intervention (counseling); Computer science; Management science; Risk analysis (engineering); Operations research; Business; Knowledge management; Engineering; Psychology; Marketing","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":[],"consensus_categories":[],"category_scores_codex":[0.009743891,0.0004448699,0.0004691292,0.002909411,0.0005868952,0.002377589,0.0007718156,0.001304132,0.001196201],"category_scores_gemma":[0.05156443,0.0003247413,0.0001965425,0.004035213,0.00123322,0.004695254,0.00128537,0.001194456,0.0005168045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001005356,"about_ca_system_score_gemma":0.002104569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00602926,"about_ca_topic_score_gemma":0.00642742,"domain_scores_codex":[0.9934403,0.002766293,0.0005419416,0.0009940529,0.001973613,0.0002838421],"domain_scores_gemma":[0.9513867,0.02675962,0.01024465,0.004803888,0.006164526,0.0006405342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004947061,0.0004987082,0.4445615,0.0005607961,0.0001622829,0.0001078524,0.006876848,0.01824538,0.007525096,0.03286155,0.006115944,0.4819894],"study_design_scores_gemma":[0.00007613523,0.001132496,0.8082835,0.0006809814,0.0001624582,0.000271954,0.004041795,0.06889065,0.02118576,0.07181077,0.02317064,0.0002928493],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.765088,0.002721524,0.1541268,0.003297054,0.0001871173,0.0005376332,0.001968359,0.0007238779,0.07134961],"genre_scores_gemma":[0.9586677,0.0005697829,0.03870984,0.000242125,0.00008207413,0.0002283917,0.0003800904,0.00002543862,0.001094483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009743891,"threshold_uncertainty_score":0.0515312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02692649909735303,"score_gpt":0.246461812032664,"score_spread":0.2195353129353109,"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."}}