{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":1,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":1,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"06fd4189d9cd","filters":{"venue":"RSC green chemistry series"}},"results":[{"id":"W2980682932","doi":"10.1039/9781788016353-00315","title":"Chapter 13. Metallic Wastes into New Process Catalysts: Life Cycle and Environmental Benefits within Integrated Analyses Using Selected Case Histories","year":2019,"lang":"en","type":"book-chapter","venue":"RSC green chemistry series","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Process (computing); Environmental science; Process engineering; Engineering; Computer science","authors":[{"name":"Sophie Archer","is_ca":false},{"name":"Angela J. Murray","is_ca":false},{"name":"Jacob B. Omajali","is_ca":true},{"name":"M. Paterson‐Beedle","is_ca":false},{"name":"Bhavna Sharma","is_ca":false},{"name":"Joseph Wood","is_ca":false},{"name":"Lynne E. Macaskie","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02541132850925635,"gpt":0.2394024265145285,"spread":0.2139910980052722,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001267602,0.0009588819,0.0008539943,0.00007556155,0.000314772,0.0001297323,0.0005229124,0.0004103374,0.003645984],"category_scores_gemma":[0.00003743255,0.0009301029,0.0001420953,0.0001384665,0.0007075628,0.0005709271,0.0009008569,0.0005132043,0.00009883824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007190474,"about_ca_system_score_gemma":0.0000837095,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007487015,"about_ca_topic_score_gemma":0.003625675,"domain_scores_codex":[0.9969751,0.00001958609,0.0007141171,0.001155574,0.0006631892,0.000472489],"domain_scores_gemma":[0.9980562,0.00003152306,0.0006213403,0.0008251098,0.00002315519,0.0004427267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004069983,0.001485353,0.02253688,0.01811704,0.02162143,0.01169195,0.1125674,0.3708557,0.3893069,0.007222863,0.004016284,0.03650833],"study_design_scores_gemma":[0.01238254,0.002197369,0.0009052895,0.006131315,0.02140937,0.01903611,0.07923862,0.1409702,0.395487,0.01637166,0.2671374,0.03873305],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418051,0.003544799,0.00002010725,0.0002045714,0.0001696089,0.0009397982,0.0003051513,0.0001944019,0.05281641],"genre_scores_gemma":[0.8185824,0.0001617045,0.0005326058,0.0000819394,0.0001436459,0.00001547688,0.0005468116,0.0001738347,0.1797616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2631211,"threshold_uncertainty_score":0.999315,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}