{"id":"W2253316367","doi":"10.15388/omee.2015.6.1.14226","title":"Symbiotic Vs Commensal Networking: the Case of Textile SMEs in China and Russia","year":2015,"lang":"en","type":"article","venue":"Organizations and Markets in Emerging Economies","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Typology; Business; Business networking; Sample (material); China; Criticism; Field (mathematics); Marketing; Industrial organization; Textile; Emerging markets; Knowledge management; Business model; Sociology; Computer science; Political science; Electronic business; Geography","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":[0.0004904655,0.00008741504,0.0001272959,0.000248576,0.0001129005,0.0001174531,0.00006249088,0.00002589057,0.00005483783],"category_scores_gemma":[0.00008979091,0.00007338815,0.000006860561,0.0005841878,0.00006418307,0.0002431502,0.0001809864,0.00005934019,0.000004068483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001956407,"about_ca_system_score_gemma":0.00001186096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002686217,"about_ca_topic_score_gemma":0.001128118,"domain_scores_codex":[0.9994732,0.0000147292,0.0002421773,0.0001276969,0.00002495639,0.0001172538],"domain_scores_gemma":[0.9996969,0.00003245867,0.0001007982,0.0001075019,0.00005533882,0.000007014367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002074174,0.00008073902,0.6013145,0.0001520056,0.00002281402,0.00002596634,0.001367097,0.0001709821,0.000003124786,0.3814532,0.006524065,0.008864755],"study_design_scores_gemma":[0.004121094,0.00003518635,0.6107908,0.0003127136,0.0001054238,0.00008233037,0.03007222,0.1582009,0.00002222425,0.02815472,0.1671694,0.0009329653],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9199202,0.00024093,0.00004657255,0.003045477,0.0003349626,0.0001910332,0.000001062519,0.00002540609,0.07619437],"genre_scores_gemma":[0.9990624,0.00004344579,0.00006730542,0.0003621305,0.0001282055,0.000004919078,0.000007552368,0.00001265449,0.0003113713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3532985,"threshold_uncertainty_score":0.2992682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009799021015217409,"score_gpt":0.2139719005223625,"score_spread":0.2041728795071451,"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."}}