{"id":"W2461337189","doi":"","title":"기초학문연구의 제도와 정책(2): 대학 연구 인센티브 변화 및 효과 (Changes and Effects of University Research Incentives)","year":2010,"lang":"ko","type":"article","venue":"SSRN Electronic Journal","topic":"Technology and Data Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commercialization; Context (archaeology); Incentive; Political science; Business; Higher education; Economic growth; Marketing; Economics; Market economy","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"],"consensus_categories":[],"category_scores_codex":[0.002966844,0.0002345541,0.0002921227,0.0006709162,0.0007160808,0.003829797,0.0005765859,0.001385342,0.02785847],"category_scores_gemma":[0.007284607,0.000191229,0.000741171,0.001098056,0.0007719789,0.002759903,0.000854217,0.001170975,0.001657763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00303707,"about_ca_system_score_gemma":0.002923155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004414217,"about_ca_topic_score_gemma":0.004241265,"domain_scores_codex":[0.9988295,0.0003818056,0.00009595046,0.0002192707,0.0001924198,0.0002809693],"domain_scores_gemma":[0.9920676,0.002905546,0.002473264,0.0002248166,0.001224864,0.001103981],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007193815,0.002008014,0.3834999,0.002315202,0.0006814944,0.003077667,0.00733843,0.02068119,0.01079273,0.3633865,0.04185782,0.1571673],"study_design_scores_gemma":[0.0006111409,0.001477644,0.818534,0.000506161,0.0005992983,0.0007972961,0.01438722,0.013235,0.006963874,0.06251986,0.08012354,0.0002449119],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8690177,0.002764852,0.002504124,0.01028226,0.0004322084,0.0002064792,0.001475179,0.00008784843,0.1132293],"genre_scores_gemma":[0.985517,0.000347368,0.0003665947,0.0004633637,0.00005418903,0.00006501487,0.0001266948,0.000009713242,0.01305014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9970332,"threshold_uncertainty_score":0.09319586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008055285167526663,"score_gpt":0.2587795077167013,"score_spread":0.2507242225491746,"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."}}