{"id":"W2557536260","doi":"10.5539/ibr.v9n12p165","title":"Challenges of Innovation for Chinese Small and Medium-sized Enterprises: Case Study in Beijing","year":2016,"lang":"en","type":"article","venue":"International Business Research","topic":"Economic and Technological Innovation","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prosperity; Business; Beijing; Economic shortage; Government (linguistics); China; Small and medium-sized enterprises; Marketing; Industrial organization; Sustainable development; Finance; Economic growth; Economics; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001879637,0.00007872239,0.000215889,0.00124428,0.00003912296,0.00002860384,0.0002173524,0.00007933402,0.00005210305],"category_scores_gemma":[0.002478166,0.00006319408,0.00001544646,0.0007074236,0.00009497635,0.0002270844,0.0001454208,0.00009469267,0.000009163796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001043484,"about_ca_system_score_gemma":0.00002564423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002503143,"about_ca_topic_score_gemma":0.0004338107,"domain_scores_codex":[0.9987755,0.00001653198,0.0006831563,0.0003155316,0.0000535174,0.0001557731],"domain_scores_gemma":[0.9985915,0.0003986354,0.0002085569,0.0001509147,0.0006363788,0.00001401735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008391179,0.0002942874,0.8150542,0.00003539365,0.00003926671,0.00003001965,0.0001928577,0.000002360009,0.0004790265,0.1639573,0.00001438231,0.01981692],"study_design_scores_gemma":[0.002696557,0.0001328994,0.8615758,0.00007110505,9.210733e-7,0.00003536429,0.0007657835,0.0002502196,0.0001304585,0.1335197,0.0006869379,0.0001342382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890079,0.0001799069,0.002922453,0.00527457,0.0001737277,0.0004316551,0.00004128031,0.00001438365,0.001954061],"genre_scores_gemma":[0.9990156,0.0002042111,0.000394693,0.00001587327,0.00006878206,0.0001628879,0.000005994529,0.00001021509,0.0001216975],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0465216,"threshold_uncertainty_score":0.2966776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.228026172879452,"score_gpt":0.3814138499405632,"score_spread":0.1533876770611112,"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."}}