{"id":"W4322503881","doi":"10.1111/emre.12563","title":"Effects of human capital and learning rate: When organizations meet with information distortion and environmental dynamism","year":2023,"lang":"en","type":"article","venue":"European Management Review","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Natural Science Foundation of China","keywords":"Dynamism; Organizational learning; Misrepresentation; Distortion (music); Forgetting; Human capital; Organizational performance; Knowledge management; Business; Economics; Psychology; Marketing; Cognitive psychology; Computer science; 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":[],"consensus_categories":[],"category_scores_codex":[0.0006345595,0.0001466243,0.0001609726,0.0002660242,0.0002357722,0.000123534,0.00009282543,0.00001029449,0.00004796373],"category_scores_gemma":[0.00003907024,0.0001276409,0.00001742916,0.0005425063,0.00004898671,0.0006803953,0.0003183633,0.00006485334,0.0002559249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001864074,"about_ca_system_score_gemma":0.000001197204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005616465,"about_ca_topic_score_gemma":0.000003201679,"domain_scores_codex":[0.9991804,0.00005569527,0.0003041656,0.0001677048,0.0001615798,0.0001304745],"domain_scores_gemma":[0.9995593,0.00001195003,0.000253706,0.0001232569,0.00004101435,0.00001070342],"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":[0.00002971213,0.0002517518,0.02078279,0.09280849,0.0005436045,0.0001204603,0.001670358,0.00004999755,0.0006209996,0.6743204,0.02539321,0.1834082],"study_design_scores_gemma":[0.003402798,0.0001613125,0.3561974,0.00656632,0.001587708,0.000003827968,0.002854429,0.001501941,0.0000393762,0.001323137,0.6251466,0.001215156],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3651986,0.006214183,0.003526746,0.001534104,0.0003439726,0.004676258,0.0000051771,0.0009271495,0.6175738],"genre_scores_gemma":[0.9934263,0.003103735,0.00007220336,0.001022544,0.00006257473,0.00002117916,0.0004303161,0.00002941011,0.001831755],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6729972,"threshold_uncertainty_score":0.5205043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00381013391964976,"score_gpt":0.1775799161385462,"score_spread":0.1737697822188964,"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."}}