{"id":"W2021383537","doi":"10.1177/016555150002600305","title":"Regional business intelligence: the view from Canada","year":2000,"lang":"en","type":"article","venue":"Journal of Information Science","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Université de Montréal; Australian Government","keywords":"Government (linguistics); Business; Panorama; Dissemination; Knowledge management; Public relations; Business intelligence; Marketing; Political science; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.000743542,0.0000728078,0.00009596156,0.0001570575,0.0002843093,0.0004366022,0.0007944084,0.00001327706,0.001657884],"category_scores_gemma":[0.000285232,0.00004391072,0.00003215163,0.001445663,0.0001923215,0.006449625,0.0000512827,0.000123779,0.0003578867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007414731,"about_ca_system_score_gemma":0.0006675749,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06494472,"about_ca_topic_score_gemma":0.02064335,"domain_scores_codex":[0.9985926,0.00000449418,0.0004697446,0.00005323136,0.0007376993,0.0001422259],"domain_scores_gemma":[0.9977878,0.00007095785,0.0003772632,0.0001258931,0.001621212,0.00001691833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007247512,0.0000347439,0.004151485,0.00003955074,0.00001573633,0.000009066744,0.0006869215,0.003284218,0.00009713179,0.02669727,0.02393902,0.9409724],"study_design_scores_gemma":[0.00005661022,0.000004186752,0.05107706,0.00009932545,0.000008961734,0.00002195987,0.000682828,0.003204911,0.0001775959,0.002233132,0.9423356,0.00009779323],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7984815,0.0004928976,0.0147152,0.01343023,0.002733174,0.000219749,0.000004695706,0.00002425429,0.1698983],"genre_scores_gemma":[0.9928349,0.0001358109,0.0001419655,0.006144959,0.0006515945,9.336122e-7,0.000001717598,0.000001964976,0.00008613148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9408746,"threshold_uncertainty_score":0.9992548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02058469456448512,"score_gpt":0.2411443067736467,"score_spread":0.2205596122091616,"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."}}