{"id":"W140296449","doi":"10.1007/978-1-4615-1535-7_9","title":"Knowledge Management at NRC","year":2001,"lang":"en","type":"book-chapter","venue":"Economics of science, technology and innovation","topic":"Research, Science, and Academia","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001367216,0.0004326113,0.0006282146,0.001322214,0.001605218,0.004406903,0.0009015163,0.001737304,0.2246794],"category_scores_gemma":[0.001719701,0.000261078,0.0002444327,0.001823459,0.0007319388,0.002368872,0.0009796891,0.001545421,0.1037113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005345988,"about_ca_system_score_gemma":0.004189933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01696891,"about_ca_topic_score_gemma":0.04283238,"domain_scores_codex":[0.999076,0.00009206832,0.00002803852,0.00021511,0.0004772815,0.0001116013],"domain_scores_gemma":[0.9988833,0.0001710012,0.0000459849,0.0001764581,0.0003894996,0.0003337256],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003102519,0.00005167259,0.0002708837,0.00007906951,0.000003271191,0.0001056054,0.0002450782,0.0004250334,0.0008026169,0.05353175,0.6302902,0.3141638],"study_design_scores_gemma":[0.000002810904,0.000007269663,0.0003841304,0.00003844955,0.000001325386,0.00002950245,0.00004017882,0.0003129262,0.0003332284,0.004665045,0.9941795,0.000005665773],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.002917997,0.004912597,0.004763265,0.01175506,0.001628427,0.00004936765,0.0009162675,0.00122035,0.9718367],"genre_scores_gemma":[0.003736856,0.0007724484,0.001111037,0.0003063307,0.0001281,0.000008697112,0.000180266,0.00009545622,0.9936609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9986328,"threshold_uncertainty_score":0.7516274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09178925548830505,"score_gpt":0.3634994458150497,"score_spread":0.2717101903267447,"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."}}