{"id":"W7131917948","doi":"","title":"从流动水果摊到年收20亿的逆袭","year":2017,"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":"","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0001934611,0.0003826582,0.0003372221,0.0001280891,0.004920688,0.0003040138,0.001189733,0.0006157043,0.0001511452],"category_scores_gemma":[0.0002017006,0.000423461,0.0002127196,0.00005266532,0.002382682,0.0009946922,0.0002336831,0.000780313,0.0003825531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002509202,"about_ca_system_score_gemma":0.0004656185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001207173,"about_ca_topic_score_gemma":0.0000224862,"domain_scores_codex":[0.9981461,0.00003066798,0.0004971189,0.0004956361,0.0003380954,0.0004924175],"domain_scores_gemma":[0.9979013,0.00004489408,0.0001506487,0.001626224,0.0001091291,0.0001677913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004699635,0.0001024508,0.00456893,0.0002265382,0.0002966549,0.001311569,0.0001830952,0.006246597,0.004317502,0.9749873,0.002014838,0.005697492],"study_design_scores_gemma":[0.003437666,0.0004841464,0.4469545,0.00172259,0.0005142633,0.003892379,0.0008102785,0.02851957,0.0326664,0.1681829,0.3089929,0.003822358],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1477956,0.008771227,0.001285013,0.0003226511,0.008887946,0.000179989,0.00002654617,0.0003682143,0.8323628],"genre_scores_gemma":[0.9920979,0.0005840045,0.0006539878,0.00003227081,0.0009549872,0.00002926359,0.000009905623,0.00002539035,0.005612329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8443022,"threshold_uncertainty_score":0.9998217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01396809832597967,"score_gpt":0.2290408715450762,"score_spread":0.2150727732190965,"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."}}