{"id":"W7132427495","doi":"","title":"两鲜求解生鲜电商消费升级","year":2018,"lang":"","type":"article","venue":"CEIBS Institutional Repository","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Casa","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0103845,0.0006658997,0.0007291141,0.004355625,0.003371869,0.01801607,0.001566726,0.001759649,0.03095545],"category_scores_gemma":[0.03819539,0.0004606046,0.0005788626,0.005265533,0.006258777,0.01171984,0.002452481,0.002849087,0.005940306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00896446,"about_ca_system_score_gemma":0.011411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0180571,"about_ca_topic_score_gemma":0.009046664,"domain_scores_codex":[0.9931457,0.002321417,0.0005500178,0.001248765,0.002218031,0.000516032],"domain_scores_gemma":[0.9848941,0.007798039,0.001268087,0.0009798798,0.004302748,0.0007571004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001615101,0.0001240576,0.01703296,0.0004774355,0.0001014421,0.0001076402,0.007633482,0.003278078,0.0006016662,0.7850056,0.03065446,0.1548216],"study_design_scores_gemma":[0.00008744997,0.0001516669,0.02682646,0.001109402,0.0001942881,0.0003141536,0.01915495,0.004870753,0.003383718,0.6981449,0.2456039,0.0001583037],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09215645,0.009175574,0.03952071,0.03006084,0.001156271,0.0002360433,0.002387022,0.0005854459,0.8247216],"genre_scores_gemma":[0.9302057,0.003885759,0.01980595,0.001937134,0.0005606824,0.000413482,0.0007026641,0.0002585632,0.04223012],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03095545,"threshold_uncertainty_score":0.1035563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009570343744625495,"score_gpt":0.2121716146140548,"score_spread":0.2026012708694293,"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."}}