{"id":"W4254741545","doi":"10.1002/div.3643","title":"Sherwin‐Williams Co.","year":2006,"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":[0.0004817572,0.002108802,0.0009296989,0.003895309,0.001574206,0.002815103,0.001478937,0.001475653,0.7721315],"category_scores_gemma":[0.001239533,0.0009076828,0.0005080282,0.002559416,0.000654434,0.002287286,0.002088387,0.002098942,0.6860783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009347858,"about_ca_system_score_gemma":0.001477268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004064266,"about_ca_topic_score_gemma":0.01114506,"domain_scores_codex":[0.9992016,0.00004365238,0.00003831337,0.0002194528,0.0004325032,0.00006442002],"domain_scores_gemma":[0.9988388,0.0001335088,0.00007904584,0.0002174672,0.0005393947,0.0001917422],"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":[0.0001446225,0.0001803788,0.0005308681,0.0004357546,0.00001303894,0.0004078988,0.0001377603,0.000200786,0.006399948,0.01000858,0.4203047,0.5612358],"study_design_scores_gemma":[0.00001429446,0.00004407571,0.0006686696,0.0001392848,0.000005804102,0.0003805683,0.00005193333,0.0001192868,0.00107345,0.0009110472,0.9965834,0.000008277457],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001193689,0.004003959,0.002606726,0.0008336455,0.0004828639,0.0001431804,0.002279138,0.002934691,0.9855222],"genre_scores_gemma":[0.00227819,0.001474261,0.00114638,0.0001924972,0.00003916764,0.00004035088,0.001178433,0.0002967898,0.993354],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7721315,"threshold_uncertainty_score":0.3250268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005410277139403218,"score_gpt":0.2000039226514203,"score_spread":0.194593645512017,"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."}}