{"id":"W2981119880","doi":"10.1017/mor.2019.34","title":"An Anatomy of Bengaluru's ICT Cluster: A Community Detection Approach","year":2019,"lang":"en","type":"article","venue":"Management and Organization Review","topic":"Innovation and Socioeconomic Development","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Information and Communications Technology; Cluster (spacecraft); Horizontal and vertical; Business; Economic geography; Community structure; Knowledge management; Industrial organization; Bridge (graph theory); Relation (database); Network analysis; Marketing; Economics; Computer science; Geography; Ecology; Data mining; Engineering","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":[0.0007359798,0.0001129701,0.000208294,0.0001607726,0.000159746,0.00008535232,0.0001599824,0.00003365383,0.0004426527],"category_scores_gemma":[0.00001670939,0.0001083359,0.000020994,0.0006769511,0.0000187846,0.0005520632,0.0001320928,0.00008632046,0.0001361942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002464105,"about_ca_system_score_gemma":0.000004739043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003185265,"about_ca_topic_score_gemma":0.000005053483,"domain_scores_codex":[0.99928,0.00003659688,0.0003227144,0.0001494761,0.0001145989,0.00009663592],"domain_scores_gemma":[0.9993393,0.00000688671,0.0002294068,0.000244696,0.0001720189,0.000007620135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002414484,0.000779105,0.4567356,0.05371732,0.00031928,0.000001169606,0.0007112533,0.0001072656,0.0002146421,0.2678747,0.01074868,0.2087668],"study_design_scores_gemma":[0.002495677,0.00004587961,0.5282198,0.001338097,0.0003835187,0.000003552438,0.002911888,0.006204857,0.000146603,0.001255978,0.4560304,0.0009637898],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9216135,0.001238368,0.01127196,0.0008852767,0.00042403,0.002378406,0.00000145312,0.0002348777,0.06195209],"genre_scores_gemma":[0.9921544,0.001262796,0.0004631935,0.005431245,0.00004967745,0.00001183514,0.000160782,0.00002031239,0.0004458014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4452817,"threshold_uncertainty_score":0.4846736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008921619646886578,"score_gpt":0.2239058830170837,"score_spread":0.2149842633701971,"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."}}