{"id":"W2167672468","doi":"10.5267/j.msl.2013.06.004","title":"Canonical correlation analysis between collaborative networks and innovation: A case study in information technology companies in province of Tehran, Iran","year":2013,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Canonical correlation; Business; Computer science; Correlation; Information technology; Knowledge management; Marketing; Industrial organization; Operations management; Artificial intelligence; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.004212779,0.0002020784,0.0002912531,0.002749224,0.002380582,0.001048702,0.0006115962,0.0005600189,0.0008411999],"category_scores_gemma":[0.009448974,0.0001391609,0.0004424582,0.004192761,0.001173578,0.0008259494,0.001074673,0.0004883387,0.00005619477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003537087,"about_ca_system_score_gemma":0.005880809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05001584,"about_ca_topic_score_gemma":0.08543301,"domain_scores_codex":[0.9974522,0.001380976,0.0001250951,0.0002232335,0.0004818933,0.0003365815],"domain_scores_gemma":[0.9887856,0.007412716,0.001255719,0.0003174632,0.001886448,0.0003420449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001082498,0.0005311939,0.8564457,0.0002619037,0.00007816743,0.008743817,0.05487461,0.002135457,0.0005076474,0.006394395,0.001498947,0.06841989],"study_design_scores_gemma":[0.00005043434,0.0003573373,0.7615716,0.0001712742,0.0001631335,0.003717776,0.2011698,0.02199869,0.001192091,0.003383673,0.006155457,0.00006871307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975675,0.00008887875,0.0007930832,0.0001203343,0.00000383152,0.00004740761,0.0000279271,0.000003161748,0.001347791],"genre_scores_gemma":[0.9981153,0.0001170731,0.001504771,0.00001349682,0.000003622704,0.00002704033,0.00003147671,0.000001443781,0.000185839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05001584,"threshold_uncertainty_score":0.0994494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01414301324547607,"score_gpt":0.2474174854528187,"score_spread":0.2332744722073427,"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."}}