{"id":"W4247666097","doi":"10.1002/div.3638","title":"RPM International Inc (DE)","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":"China; International market; Business; Geography; International trade","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":[0.00005184211,0.0000696166,0.00004706178,0.0000559592,0.0000534836,0.00003482398,0.0002524065,0.00002512385,0.0005012991],"category_scores_gemma":[0.000002863618,0.00007116599,0.00003469966,0.0001319408,0.00002382108,0.0001849882,0.00003205125,0.00006069808,0.0002570979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003533219,"about_ca_system_score_gemma":0.000009729498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008583352,"about_ca_topic_score_gemma":0.00001909294,"domain_scores_codex":[0.9994807,0.000004672334,0.0001057497,0.00009910369,0.0001342941,0.0001754932],"domain_scores_gemma":[0.9998062,0.000009350161,0.00001225638,0.0001166722,0.000005548819,0.00004998985],"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":[0.000006167102,0.0001931297,0.09155938,0.00002478611,0.0001194627,0.00001589811,0.0003728382,0.06226879,0.1537341,0.0384317,0.6231852,0.03008852],"study_design_scores_gemma":[0.0002476305,0.000007582557,0.07166404,0.00001070312,0.00001864255,0.000005604316,0.00006474857,0.02309466,0.05200845,0.002147713,0.8504065,0.0003237554],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8699283,0.0004248211,0.01359002,0.002562122,0.001472396,0.0001227879,0.00005865022,0.0006790854,0.1111618],"genre_scores_gemma":[0.9973526,0.00006151553,0.0005046037,0.0001017091,0.0001838425,0.00001909361,0.00003107078,0.00001101113,0.001734532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2272212,"threshold_uncertainty_score":0.5488874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004119547356990625,"score_gpt":0.1946311744359298,"score_spread":0.1905116270789391,"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."}}