{"id":"W2329586008","doi":"10.5465/ambpp.2008.33725185","title":"WHAT DOESN'T KILL YOU MAKES YOU STRONGER --DE NOVO ENTRY IN CLUSTERS.","year":2008,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Competition (biology); Productivity; Cluster (spacecraft); Economic geography; Resource (disambiguation); Biological dispersal; Contradiction; Barriers to entry; Manufacturing sector; Economics; Industrial organization; Business; Labour economics; Biology; Economic growth; Ecology; Demography; Sociology; Computer science; Market structure","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009749039,0.0002059029,0.0004337909,0.001519646,0.002475233,0.002358878,0.0006523302,0.0006438068,0.008569921],"category_scores_gemma":[0.005706724,0.0001854654,0.0003532417,0.001810792,0.001345814,0.001736402,0.001623149,0.0009104428,0.0009241492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00288075,"about_ca_system_score_gemma":0.002157676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1423496,"about_ca_topic_score_gemma":0.3425079,"domain_scores_codex":[0.9993267,0.0000908787,0.00002788009,0.000158795,0.0001536724,0.0002420912],"domain_scores_gemma":[0.9951057,0.0008631708,0.001890019,0.0004032608,0.0005643364,0.001173406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003507509,0.000172909,0.9015077,0.0001922655,0.00009795464,0.001052658,0.005651986,0.00176399,0.001543669,0.01444056,0.00933488,0.06389066],"study_design_scores_gemma":[0.0000264142,0.0001073642,0.9571177,0.00008285199,0.00005312752,0.0003903313,0.007846455,0.001255534,0.0008003634,0.006479137,0.02579748,0.00004322843],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766733,0.001020024,0.001681241,0.001442838,0.00004273822,0.00007144839,0.002281117,0.00003715655,0.01675006],"genre_scores_gemma":[0.9923604,0.000299035,0.0005754601,0.00009682358,0.00001114258,0.00001865657,0.0008173703,0.000008565239,0.005812565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1423496,"threshold_uncertainty_score":0.283042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03396751233954465,"score_gpt":0.2343637797103276,"score_spread":0.2003962673707829,"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."}}