{"id":"W7037776304","doi":"","title":"Evaluating the Impact and Value of Competitive Intelligence From The users Perspective - The Case of the National Research Councilâs Technical Intelligence Unit","year":2015,"lang":"en","type":"article","venue":"Journal of Intelligence Studies in Business","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Telus (Canada)","funders":"McGill University","keywords":"Competitive intelligence; Value (mathematics); Perspective (graphical); Quality (philosophy); Intelligence cycle; Perception; Liberian dollar; Government (linguistics); Strategic intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0277595,0.000328735,0.00028801,0.002930785,0.004890256,0.01097948,0.00112622,0.00162968,0.002613146],"category_scores_gemma":[0.05705015,0.0002683025,0.0003358564,0.002597307,0.003714622,0.006715059,0.00377319,0.00177891,0.0003706421],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00773061,"about_ca_system_score_gemma":0.005444945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01689335,"about_ca_topic_score_gemma":0.01935714,"domain_scores_codex":[0.9627548,0.02444412,0.0009977096,0.0005696351,0.008894274,0.002339454],"domain_scores_gemma":[0.9349801,0.04154877,0.003784261,0.003394942,0.01338729,0.002904715],"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":[0.0005494428,0.001149228,0.3182053,0.0004917317,0.0001238037,0.00527329,0.2379055,0.002681521,0.004737652,0.06458396,0.01063806,0.3536605],"study_design_scores_gemma":[0.00005492614,0.002240343,0.2006257,0.0008415356,0.0001680602,0.002201247,0.6605718,0.01620297,0.007844027,0.01764583,0.09131001,0.0002936165],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9241112,0.0001844399,0.002016012,0.00388455,0.00001569272,0.0001157709,0.00002906885,0.00005322902,0.0695901],"genre_scores_gemma":[0.9976828,0.00007729798,0.001148458,0.0001562813,0.000005063612,0.0000167917,0.00001132769,0.000009883644,0.0008919836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9922694,"threshold_uncertainty_score":0.1468081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4073713532603857,"score_gpt":0.5019943196789182,"score_spread":0.09462296641853246,"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."}}