{"id":"W3123015964","doi":"10.1177/0969776412474675","title":"Innovative firms behind the regions: Analysis of regional innovation performance in Portugal by external logistic biplots","year":2013,"lang":"en","type":"article","venue":"European Urban and Regional Studies","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Biplot; Conceptualization; Economic geography; Portuguese; Investment (military); Regional science; Regional policy; Business; Sample (material); Industrial organization; Process (computing); Economics; Economic system; Political science; Computer science; Geography","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":[],"consensus_categories":[],"category_scores_codex":[0.002090276,0.0003720916,0.0004649943,0.002586682,0.0004451136,0.001917445,0.0006698687,0.0005242322,0.002458723],"category_scores_gemma":[0.008865302,0.0001436515,0.001268747,0.00462555,0.0007669499,0.0006303807,0.001528408,0.0004586147,0.0004435084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009182583,"about_ca_system_score_gemma":0.0006482771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01581965,"about_ca_topic_score_gemma":0.008656826,"domain_scores_codex":[0.9984315,0.0008442228,0.00007294084,0.0002045136,0.0001890827,0.0002576679],"domain_scores_gemma":[0.9901783,0.006345259,0.001950292,0.0006197499,0.0004455727,0.0004606331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004275468,0.0001658344,0.9175138,0.0001303303,0.0002032274,0.0005980214,0.0009649381,0.05374937,0.0004996579,0.003800652,0.0007219199,0.02122473],"study_design_scores_gemma":[0.00002064099,0.000113501,0.888521,0.00004417894,0.00006061145,0.0002474503,0.002057777,0.1047088,0.0004833023,0.001571746,0.002134313,0.00003662179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923735,0.0001657831,0.002902268,0.00007892123,0.000005876441,0.00001461987,0.0008714944,0.00003440738,0.003553034],"genre_scores_gemma":[0.9983361,0.0000569874,0.000705762,0.000004314631,0.000005680277,0.00001199215,0.0005431791,0.00001103915,0.0003249462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01581965,"threshold_uncertainty_score":0.03145516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1053946284249172,"score_gpt":0.2576954424444601,"score_spread":0.1523008140195428,"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."}}