{"id":"W2916718690","doi":"10.1177/0022242919830958","title":"Market Intelligence Dissemination Practices","year":2019,"lang":"en","type":"article","venue":"Journal of Marketing","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Market intelligence; Cornerstone; Business; Dissemination; Knowledge management; Meaning (existential); Information Dissemination; Intelligence cycle; Strategic planning; Marketing; Military intelligence; Computer science; Psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004909017,0.000105577,0.0001721416,0.0002541771,0.00006111141,0.0002295862,0.0003066542,0.00003617834,0.00364986],"category_scores_gemma":[0.00656107,0.00008859452,0.0001040386,0.000317435,0.00002055693,0.001543143,0.00010837,0.0002232869,0.0003917931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003015367,"about_ca_system_score_gemma":0.00002314961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008276063,"about_ca_topic_score_gemma":0.000007448183,"domain_scores_codex":[0.9989072,0.00005883454,0.000444185,0.0001236063,0.0003057966,0.0001603862],"domain_scores_gemma":[0.9961523,0.001353514,0.001725047,0.0001148376,0.0006426056,0.00001165075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00228222,0.0003802175,0.4672469,0.001177335,0.0001442251,0.0001263996,0.0002760517,0.0001067609,0.007754165,0.007245662,0.04805931,0.4652008],"study_design_scores_gemma":[0.0002881872,0.00007896491,0.2309527,0.002741433,0.0001432013,0.0001369704,0.005366588,0.02237948,0.002023805,0.002585572,0.7327034,0.0005997361],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.508528,0.0005075634,0.002688296,0.0008282053,0.001464457,0.0001211779,2.804934e-7,0.00002112094,0.4858409],"genre_scores_gemma":[0.9939285,0.00007489573,0.0004300844,0.0001784183,0.00144361,7.89003e-7,5.613786e-7,0.00001297929,0.003930161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6846441,"threshold_uncertainty_score":0.9972609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01807793599694788,"score_gpt":0.2859612964885637,"score_spread":0.2678833604916158,"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."}}