{"id":"W4399412527","doi":"10.2166/9781789061154","title":"Metadata Collection and Organization in Wastewater Treatment and Wastewater Resource Recovery Systems","year":2024,"lang":"en","type":"book","venue":"IWA Publishing eBooks","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Public Health; Université Laval","funders":"","keywords":"Metadata; Wastewater; Resource recovery; Resource (disambiguation); Business; Computer science; Knowledge management; World Wide Web; Waste management; Engineering; Computer network","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0003911446,0.0005175961,0.0005006538,0.0003259944,0.0001697507,0.003476323,0.0002122393,0.000452992,0.00009412109],"category_scores_gemma":[0.00003056047,0.0003955261,0.0000543875,0.0001629183,0.0001329084,0.001368952,0.0005149625,0.0003241988,0.00009091054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001307504,"about_ca_system_score_gemma":0.00008114394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001365361,"about_ca_topic_score_gemma":0.0005635394,"domain_scores_codex":[0.9977006,0.0001334648,0.000455434,0.0009487018,0.0003508612,0.0004109356],"domain_scores_gemma":[0.9991955,0.00007287261,0.0001447185,0.0004095831,0.00001685942,0.0001604574],"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":[0.0008361107,0.0005467899,0.01573214,0.002191072,0.003179588,0.00225997,0.02584532,0.0007326779,0.03519762,0.002183977,0.8844414,0.0268533],"study_design_scores_gemma":[0.002473789,0.0007204619,0.0004761848,0.0009631601,0.0008835741,0.0007314979,0.0005284309,0.0004128091,0.01141435,0.002856277,0.9769748,0.001564607],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7425224,0.001688875,0.000004564576,0.0004412362,0.0009775262,0.001861635,0.0002002297,0.0002982221,0.2520054],"genre_scores_gemma":[0.02201875,0.00007227917,0.0002613471,0.00004161782,0.0002124941,0.00005682557,0.0006697527,0.0001378104,0.9765291],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7245237,"threshold_uncertainty_score":0.9998497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01384849841747187,"score_gpt":0.1926995112306284,"score_spread":0.1788510128131565,"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."}}