{"id":"W2731908294","doi":"10.22584/nr45.2017.004","title":"The State of Innovation in Sweden and its Regions","year":2017,"lang":"en","type":"article","venue":"The Northern Review","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Productivity; Position (finance); Index (typography); Field (mathematics); Data envelopment analysis; Regional science; State (computer science); Economic geography; Economics; Business; Computer science; Sociology; Economic growth; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01003512,0.00006512697,0.0002340847,0.00006321659,0.0004679513,0.0001349586,0.001211151,0.00001255008,0.00001097321],"category_scores_gemma":[0.009947119,0.00002687994,0.00004372602,0.0008441371,0.0001946091,0.000119427,0.0001610785,0.00009202237,0.00007684889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009299333,"about_ca_system_score_gemma":0.00004727179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009040876,"about_ca_topic_score_gemma":0.002714029,"domain_scores_codex":[0.9981518,0.0002863671,0.0007520556,0.0001651278,0.0005346071,0.000110075],"domain_scores_gemma":[0.9966707,0.0007600266,0.0009545583,0.001156963,0.0004444154,0.00001334648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008573173,0.00003010686,0.0207054,0.00008742526,0.00002314428,0.000002382675,0.0007455351,0.00009984695,0.0001327029,0.007831361,0.001079677,0.9692538],"study_design_scores_gemma":[0.0005366227,0.00009232814,0.3530359,0.004696114,0.0001974851,0.00002220415,0.0003037985,0.005674573,0.0002820944,0.2321482,0.4025331,0.00047762],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8538137,0.1156249,0.0001515545,0.02742801,0.00009194006,0.0004484081,0.000003971722,0.000007245407,0.002430278],"genre_scores_gemma":[0.967483,0.03048984,0.00001078318,0.000329324,0.00001171885,0.000007614435,3.532539e-7,0.000004287596,0.001663095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9687762,"threshold_uncertainty_score":0.9983925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1791889928847837,"score_gpt":0.4328032373055133,"score_spread":0.2536142444207297,"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."}}