{"id":"W2040667363","doi":"10.1142/9789812772572_0007","title":"CROSS-ANALYSIS OF DATA COLLECTED ON KNOWLEDGE MANAGEMENT PRACTICES IN CANADIAN FORCES ENVIRONMENTS","year":2006,"lang":"en","type":"article","venue":"","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data science; Knowledge management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004949972,0.0004181371,0.0005567019,0.01123574,0.005580052,0.002330563,0.001072176,0.0006403261,0.001597788],"category_scores_gemma":[0.02439955,0.0003167919,0.0004103692,0.02210717,0.001459372,0.001006871,0.002473541,0.0005780769,0.0002512663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02896125,"about_ca_system_score_gemma":0.03163484,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9564508,"about_ca_topic_score_gemma":0.9821082,"domain_scores_codex":[0.9918535,0.001014873,0.0005243422,0.000712585,0.004351722,0.001542932],"domain_scores_gemma":[0.970427,0.005659913,0.002772479,0.001200617,0.01820022,0.001739765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003414493,0.0002816957,0.8325945,0.0003931575,0.000243367,0.0004345292,0.09630749,0.0005197346,0.002170644,0.0009089918,0.004213311,0.06159119],"study_design_scores_gemma":[0.000003189555,0.00004797526,0.9632475,0.00006735493,0.00002326004,0.00003457384,0.03045859,0.0002068066,0.0003188345,0.00003113025,0.005532842,0.00002778134],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917066,0.0002494298,0.000345768,0.000129102,0.00001393649,0.0001924067,0.003500035,0.00001272553,0.003849945],"genre_scores_gemma":[0.9900564,0.0004919342,0.001466012,0.0001031233,0.000009308006,0.0002978067,0.005439063,0.00001528563,0.002120974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04354924,"threshold_uncertainty_score":0.2101296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05451716342667799,"score_gpt":0.3252333228100903,"score_spread":0.2707161593834123,"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."}}