{"id":"W4238300065","doi":"10.1002/div.3239","title":"Sherwin‐Williams Co.","year":2005,"lang":"en","type":"article","venue":"Mergent s Dividend Achievers","topic":"Polymer Science and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Automotive industry; Variety (cybernetics); Engineering; Advertising; Commerce; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004779491,0.002066989,0.0009149995,0.00391344,0.001576557,0.00285603,0.001467596,0.001464276,0.774717],"category_scores_gemma":[0.00121988,0.0009118267,0.0005035095,0.002508002,0.0006511181,0.002267458,0.002097767,0.002071051,0.6881744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009438692,"about_ca_system_score_gemma":0.001501003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004110185,"about_ca_topic_score_gemma":0.01137611,"domain_scores_codex":[0.9992055,0.00004298894,0.00003811974,0.0002145402,0.0004343356,0.00006454579],"domain_scores_gemma":[0.9988624,0.0001289656,0.00007708089,0.0002104335,0.0005300404,0.0001911989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001414181,0.0001804987,0.0005236727,0.0004330561,0.00001283799,0.0004050206,0.000136273,0.0002000745,0.006423894,0.01007425,0.4271935,0.5542755],"study_design_scores_gemma":[0.00001396586,0.00004303542,0.0006495009,0.0001376499,0.000005661629,0.0003726933,0.00005131152,0.0001170872,0.001058904,0.000903047,0.9966389,0.000008184013],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001148571,0.003797564,0.00249956,0.0008187564,0.0004699245,0.0001394534,0.002196756,0.002849303,0.98608],"genre_scores_gemma":[0.002213591,0.001443511,0.00109942,0.0001896411,0.00003875404,0.00003870753,0.00115163,0.0002868056,0.993538],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.774717,"threshold_uncertainty_score":0.3213389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009627201494745597,"score_gpt":0.2309389981214001,"score_spread":0.2213117966266545,"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."}}