{"id":"W2045234370","doi":"10.1109/icsssm.2010.5530213","title":"Evaluating global technology transfer research performance","year":2010,"lang":"en","type":"article","venue":"","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Technology transfer; Computer science; Data science; Knowledge transfer; Transfer (computing); Knowledge management; Operations research; Engineering","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.03450991,0.0007438443,0.001281916,0.05286524,0.0009218911,0.005985897,0.0007013421,0.0009100361,0.004765707],"category_scores_gemma":[0.1019563,0.0001535978,0.001305433,0.06986127,0.001106491,0.008152022,0.003773432,0.0005073395,0.001289553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001998662,"about_ca_system_score_gemma":0.001545249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001594281,"about_ca_topic_score_gemma":0.001459219,"domain_scores_codex":[0.9771042,0.006116468,0.003642595,0.001654285,0.01043247,0.001049902],"domain_scores_gemma":[0.8612136,0.07259282,0.02402549,0.008305852,0.03028721,0.003575005],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003923484,0.0002169586,0.7520679,0.001141981,0.001334413,0.0002811847,0.002662208,0.008432657,0.001575897,0.00644382,0.003815054,0.2216356],"study_design_scores_gemma":[0.00004980831,0.0008578527,0.9577715,0.0002748598,0.0007205391,0.0004303984,0.006813671,0.009476991,0.003171266,0.004926857,0.01540763,0.00009879405],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9235377,0.00555592,0.006400749,0.0009494581,0.0001308951,0.0002616082,0.005547086,0.0003023258,0.05731416],"genre_scores_gemma":[0.9889876,0.001480426,0.003806328,0.0000392587,0.0001491997,0.0001774203,0.003577548,0.00007551654,0.001706693],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9654901,"threshold_uncertainty_score":0.1825081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1129738433788023,"score_gpt":0.3930070352576312,"score_spread":0.2800331918788289,"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."}}