{"id":"W2328894012","doi":"10.4018/ijkm.2015070101","title":"Knowledge Identification and Acquisition in SMEs","year":2015,"lang":"en","type":"article","venue":"International Journal of Knowledge Management","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Roads University","funders":"","keywords":"Identification (biology); Knowledge management; Business; Knowledge acquisition; Flexibility (engineering); Empirical evidence; Knowledge value chain; Empirical research; Balance (ability); Knowledge creation; Marketing; Organizational learning; Computer science; Management; Psychology; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.002374738,0.00009758006,0.0001464888,0.0007649622,0.00007500863,0.000206551,0.0005290855,0.00004535513,0.00004134007],"category_scores_gemma":[0.0001303481,0.00009917113,0.00005844258,0.0002938881,0.00009277464,0.0005691844,0.0002253306,0.0001103258,0.0001008138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004177381,"about_ca_system_score_gemma":0.0000740585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002668633,"about_ca_topic_score_gemma":0.0004455552,"domain_scores_codex":[0.9985682,0.0001662163,0.0004897949,0.0001531124,0.0004503159,0.0001723048],"domain_scores_gemma":[0.9988466,0.00005766009,0.0002333504,0.00008688455,0.0006467733,0.0001287406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001930131,0.0009595462,0.04151309,0.00007741213,0.0004644048,0.0001991829,0.06282344,0.00005953759,0.00006374563,0.4597664,0.0215743,0.412306],"study_design_scores_gemma":[0.004258034,0.0001175822,0.08206801,0.0005318413,0.0001373088,0.00001617428,0.03864614,0.001039335,0.0001348671,0.03287304,0.8397307,0.0004469233],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1400961,0.004356069,0.002828413,0.00237256,0.005524557,0.0003564646,0.000001674174,0.00004256791,0.8444216],"genre_scores_gemma":[0.9894727,0.0006281126,0.0003444782,0.0000330693,0.0006851908,0.000007432334,0.000002839924,0.000008859252,0.008817323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8493766,"threshold_uncertainty_score":0.4044081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04689544269396651,"score_gpt":0.3603095034913605,"score_spread":0.313414060797394,"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."}}