{"id":"W4245707504","doi":"10.1002/div.1650","title":"Sherwin‐Williams Co.","year":2004,"lang":"en","type":"article","venue":"Mergent s Dividend Achievers","topic":"Legal Cases and Commentary","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Variety (cybernetics); Automotive industry; Business; Engineering; 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":[0.0002501777,0.0008322143,0.0003092914,0.001754601,0.002091091,0.002417977,0.0009298234,0.002449947,0.7154257],"category_scores_gemma":[0.001227591,0.0004848875,0.000240048,0.001413371,0.0007816781,0.001690984,0.001401086,0.002268575,0.4686334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001370442,"about_ca_system_score_gemma":0.001245221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009493208,"about_ca_topic_score_gemma":0.0275886,"domain_scores_codex":[0.999615,0.0000339535,0.00001921086,0.00009901628,0.00018793,0.00004490555],"domain_scores_gemma":[0.9995412,0.0001096766,0.00003461108,0.00007215136,0.0001778135,0.00006468414],"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":[0.00005501652,0.00004416757,0.0001812507,0.0001858273,0.000003478553,0.0003043801,0.0001568356,0.00007102367,0.0009650411,0.03429213,0.7741103,0.1896305],"study_design_scores_gemma":[0.00000350181,0.000005340687,0.0001721758,0.00008111119,7.535502e-7,0.00008579559,0.00004627637,0.0000209334,0.00009535421,0.0007632136,0.9987236,0.000001929033],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002767251,0.00272994,0.0001946837,0.001717007,0.0004260902,0.00003202456,0.0003047738,0.0002130925,0.9941057],"genre_scores_gemma":[0.001407796,0.001000897,0.0001153325,0.0005443296,0.00004147402,0.00001526642,0.0001111999,0.00003860996,0.9967251],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7154257,"threshold_uncertainty_score":0.4059107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01937823853728856,"score_gpt":0.2956230805606888,"score_spread":0.2762448420234002,"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."}}