{"id":"W4401433168","doi":"10.1177/00420980241264715","title":"Firm dynamics in urban neighbourhoods and innovation: A microgeographic analysis","year":2024,"lang":"en","type":"article","venue":"Urban Studies","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Externality; Neighbourhood (mathematics); Economic geography; Quarter (Canadian coin); Panel data; Diversity (politics); Economics; Work (physics); Dynamics (music); Business; Microeconomics; Econometrics; Sociology; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004087853,0.0001727863,0.0006384609,0.0026624,0.0000923322,0.0001445705,0.0001095759,0.0000691413,0.00005646203],"category_scores_gemma":[0.00004912208,0.0001813874,0.0001982773,0.004337217,0.0001186833,0.0001599794,0.00008923913,0.0001332962,0.00004289017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001816659,"about_ca_system_score_gemma":0.00001156411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005084549,"about_ca_topic_score_gemma":0.002005833,"domain_scores_codex":[0.9985471,0.000009065464,0.0006965166,0.000503364,0.00002785167,0.0002160997],"domain_scores_gemma":[0.999507,0.00007987153,0.0001388522,0.0001967185,0.00004386514,0.0000337444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002496437,0.00001527728,0.5068979,0.0000265734,0.001426502,0.000006690181,0.0003959928,0.00003909424,4.517633e-7,0.4897831,0.0009064263,0.0004995518],"study_design_scores_gemma":[0.0006554593,0.0001179896,0.3722329,0.00008984433,0.0005704063,0.000006523214,0.001507192,0.2848438,0.000005394692,0.2500653,0.08882073,0.001084371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.858036,0.1289744,0.0008028868,0.004529162,0.0002635315,0.0001191228,0.0001670494,0.00004877425,0.007059086],"genre_scores_gemma":[0.9937968,0.004306186,0.0001520807,0.0002123044,0.00009433059,0.0000276005,0.00004352631,0.00001518128,0.001351971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2848047,"threshold_uncertainty_score":0.7396761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0329823696246017,"score_gpt":0.2469819311416245,"score_spread":0.2139995615170228,"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."}}