{"id":"W1950755087","doi":"10.1520/stp10881s","title":"Field Exposure Results on Trends in Atmospheric Corrosion and Pollution","year":2002,"lang":"en","type":"book-chapter","venue":"","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Environmental science; Atmospheric pollution; Field (mathematics); Pollution; Corrosion; Metallurgy; Materials science; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0003222177,0.0001818017,0.0001255614,0.001327537,0.0000969999,0.0002960195,0.0002084299,0.0001731191,0.005811766],"category_scores_gemma":[0.0004390033,0.00007376622,0.0001454305,0.001545711,0.0001168546,0.0002402291,0.0001430273,0.0001506589,0.0009192287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003431195,"about_ca_system_score_gemma":0.0001109851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002626676,"about_ca_topic_score_gemma":0.003920221,"domain_scores_codex":[0.9997979,0.00003001033,0.00001087412,0.00004386468,0.0001070944,0.00001031902],"domain_scores_gemma":[0.9995364,0.0001994598,0.0000526084,0.00003032205,0.0001666805,0.00001453987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000968414,0.0004927766,0.2006892,0.001288832,0.0001469843,0.001074777,0.003457855,0.006921798,0.07870193,0.003045961,0.0304031,0.6728085],"study_design_scores_gemma":[0.00001584682,0.00127298,0.8843287,0.000104098,0.00006927452,0.001209597,0.0007439858,0.0009308691,0.02751307,0.0010485,0.08273116,0.00003207964],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8699195,0.007643954,0.004036802,0.0002372778,0.00007800279,0.00006311144,0.008505465,0.0004118575,0.109104],"genre_scores_gemma":[0.9170989,0.005850785,0.00260376,0.00009672019,0.00007576199,0.00003075712,0.007840745,0.00008815296,0.06631437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005811766,"threshold_uncertainty_score":0.01944232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01086778375547878,"score_gpt":0.1960003720786621,"score_spread":0.1851325883231833,"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."}}