{"id":"W2048184110","doi":"10.1007/s10109-006-0029-6","title":"Geographic clustering of firms and urban form: a multivariate analysis","year":2006,"lang":"en","type":"article","venue":"Journal of Geographical Systems","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Metropolitan area; Cluster analysis; Economic geography; Geography; Decentralization; Regional science; Relation (database); Work (physics); Space (punctuation); Spatial analysis; Cluster (spacecraft); Economics; Computer science; Data mining; Statistics; Engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001054722,0.0001633823,0.001146059,0.001701082,0.00007784914,0.0001010565,0.0002227964,0.0001362497,0.00002960345],"category_scores_gemma":[0.00003340417,0.0001468006,0.0008860824,0.001081917,0.0001114302,0.0001994802,0.00004980481,0.0001752507,0.000002732039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000245717,"about_ca_system_score_gemma":0.000009159092,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01057672,"about_ca_topic_score_gemma":0.0004230916,"domain_scores_codex":[0.9975709,0.00002971335,0.001839103,0.000238722,0.00009180648,0.000229752],"domain_scores_gemma":[0.9975936,0.00008896986,0.001852396,0.0002042905,0.0001306475,0.0001300408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003643675,0.0000999879,0.9411494,0.00004750543,0.001518222,0.000006409118,0.00004604772,0.007907742,0.0000301995,0.04901474,0.00005389436,0.00008948467],"study_design_scores_gemma":[0.0009393225,0.0002101368,0.8259102,0.00005159268,0.0004150897,0.00003527031,0.00006339127,0.153016,0.000003749474,0.01457548,0.004493908,0.0002859016],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.968245,0.006617901,0.02352126,0.0003775808,0.0002441358,0.0001022664,0.00006033829,0.000006539034,0.0008249369],"genre_scores_gemma":[0.9988135,0.0004949276,0.0003810425,0.00001881956,0.0002046786,0.000003413243,0.000006007977,0.00001220049,0.00006540525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1451083,"threshold_uncertainty_score":0.9960119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01292596583396092,"score_gpt":0.1989878162057551,"score_spread":0.1860618503717942,"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."}}