{"id":"W4256570547","doi":"10.1002/div.6180","title":"Wal‐Mart Stores, Inc.","year":2007,"lang":"en","type":"article","venue":"Mergent s Dividend Achievers","topic":"ICT Impact and Policies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Club; Business; China; Commerce; Advertising; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002648977,0.0001804132,0.0001456597,0.0001376139,0.00008725416,0.00002555514,0.0001839733,0.00007791557,0.0005647293],"category_scores_gemma":[0.00001915077,0.0001731024,0.00007479877,0.0001700811,0.00003323164,0.0001627281,0.00003956166,0.0001687086,0.0005147265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008759386,"about_ca_system_score_gemma":0.000009539543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001886742,"about_ca_topic_score_gemma":0.0001324366,"domain_scores_codex":[0.9989963,0.00001226349,0.0002044379,0.00006665047,0.0002249775,0.000495424],"domain_scores_gemma":[0.9995247,0.00004602583,0.00002084088,0.0002129417,0.00001153269,0.0001840143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009709158,0.0001613265,0.08836281,0.0002356501,0.0005917572,0.00006099352,0.01539188,0.01097247,0.03651999,0.006213219,0.8049609,0.03643192],"study_design_scores_gemma":[0.0003551296,0.00004462004,0.08084291,0.00002235881,0.0000391787,0.000007361631,0.000559558,0.0002664333,0.01615528,0.0001312367,0.9011177,0.0004581896],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768825,0.0006620418,0.001238785,0.0002114857,0.00198352,0.0001048229,0.00002133133,0.0004285055,0.01846698],"genre_scores_gemma":[0.997749,0.0001440029,0.00007470389,0.0001922018,0.0003155356,0.00000316867,0.00002455329,0.00003936547,0.001457509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09615684,"threshold_uncertainty_score":0.7058912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01064720623469587,"score_gpt":0.2321862972252068,"score_spread":0.221539090990511,"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."}}