{"id":"W2921654638","doi":"10.1111/grow.12291","title":"Diverse diversities—Open innovation in small towns and rural areas","year":2019,"lang":"en","type":"article","venue":"Growth and Change","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Urban agglomeration; Diversity (politics); Economic geography; Variety (cybernetics); Work (physics); Rural area; Business; Geography; Economies of agglomeration; Regional science; Economic growth; Economics; Sociology; Political science","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":[0.0005743073,0.00009297874,0.0001843889,0.001941737,0.001077267,0.001465295,0.0002657317,0.0003230528,0.00304688],"category_scores_gemma":[0.002732645,0.00009599809,0.000114203,0.001528971,0.002076472,0.0007719061,0.002305951,0.0002912254,0.000167293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000733135,"about_ca_system_score_gemma":0.0002897534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002810466,"about_ca_topic_score_gemma":0.006965998,"domain_scores_codex":[0.999405,0.0001763498,0.00001802568,0.0001088507,0.0001538889,0.0001378273],"domain_scores_gemma":[0.9960104,0.001586872,0.001189621,0.0002352558,0.0003190401,0.0006588288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004255496,0.0002595257,0.8900581,0.0001319431,0.00005485057,0.001695124,0.03217097,0.002355991,0.01231452,0.01677162,0.0005830742,0.04317874],"study_design_scores_gemma":[0.00001211935,0.0001629749,0.9722086,0.00002385541,0.00001233408,0.0006136181,0.01736948,0.001254299,0.001083811,0.004208918,0.003034021,0.00001579983],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963936,0.0000357491,0.0001883041,0.0000408509,6.739833e-7,0.000004066035,0.0000194518,0.000002108542,0.003315152],"genre_scores_gemma":[0.9997843,0.00001006201,0.00004333222,0.000002807996,0.000001251601,0.000001292094,0.000007541769,4.261549e-7,0.000148934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00304688,"threshold_uncertainty_score":0.01019281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06170919058713706,"score_gpt":0.2035866633963953,"score_spread":0.1418774728092582,"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."}}