{"id":"W2980976638","doi":"","title":"An Analysis of Marketing Channels of Biological Reagentsin China and Canada","year":2014,"lang":"zh","type":"article","venue":"亚洲社会药学","topic":"Corporate Identity and Reputation","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"China; Business; Marketing; Geography; Political science; Law","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":[0.000573154,0.0001835737,0.0002193716,0.003195281,0.002931985,0.003136897,0.0005086324,0.0004470083,0.004074384],"category_scores_gemma":[0.002190211,0.0001541122,0.0002326334,0.00501554,0.001185092,0.0007611978,0.0009060101,0.0004926851,0.0001939125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02922363,"about_ca_system_score_gemma":0.02272782,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9309232,"about_ca_topic_score_gemma":0.9599745,"domain_scores_codex":[0.999208,0.00006519902,0.00001733112,0.00006446383,0.000307115,0.0003379313],"domain_scores_gemma":[0.9961686,0.0008556823,0.0007103265,0.00008182185,0.001530358,0.00065324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005486704,0.0001584213,0.8882243,0.0001856791,0.00009036169,0.001752673,0.01847487,0.001354788,0.00428153,0.02470794,0.007508549,0.05271219],"study_design_scores_gemma":[0.00001182071,0.00004075343,0.9595942,0.00004304375,0.00004736357,0.00009722239,0.0186379,0.002310977,0.001117314,0.0003612085,0.01770074,0.00003741932],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833428,0.0005518951,0.0001377501,0.0004927556,0.000005970736,0.00002692784,0.0006244009,0.00001389692,0.0148036],"genre_scores_gemma":[0.9956285,0.0002337707,0.00007734235,0.00003829378,0.000002788748,0.000004068077,0.0001826369,0.000003928046,0.003828757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06907684,"threshold_uncertainty_score":0.2120333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01378570717159423,"score_gpt":0.211407786174708,"score_spread":0.1976220790031138,"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."}}