{"id":"W7062594106","doi":"","title":"Treatment of Aqueous Arsenic Using Chemically and Electrochemically Modified Biomaterials","year":2023,"lang":"en","type":"dissertation","venue":"University Library (University of Saskatchewan)","topic":"Scientific Measurement and Uncertainty Evaluation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Adsorption; Arsenic; Sorption; Contamination; Biomass (ecology); Water treatment; Aqueous solution; Human decontamination","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004086475,0.0002861214,0.0007688503,0.0009320395,0.0002265764,0.0000628207,0.0008286639,0.0003824615,0.0006380453],"category_scores_gemma":[0.00008759872,0.0003145419,0.0003127503,0.001162941,0.0002453473,0.0007021364,0.0001319205,0.00006823558,0.00002779087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001353018,"about_ca_system_score_gemma":0.0008217213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009069628,"about_ca_topic_score_gemma":0.0007824939,"domain_scores_codex":[0.9972162,0.0002034474,0.0004110971,0.0007424339,0.001153673,0.0002731078],"domain_scores_gemma":[0.9977267,0.0003407437,0.0008953217,0.0005141521,0.0003600592,0.0001630509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"qualitative","study_design_scores_codex":[0.002585946,0.0002753851,0.00144307,0.0001446151,0.000388402,0.00008155202,0.04143212,0.00006595067,0.9395884,0.00009504663,0.001282016,0.01261746],"study_design_scores_gemma":[0.005754103,0.000867198,0.007264814,0.0004200871,0.001392048,0.00001209071,0.4965491,0.006779023,0.4680135,0.008664332,0.002896071,0.001387665],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970609,0.0001013425,0.0001248086,0.0001195678,0.0003475844,0.0003596245,0.0001647925,0.00008223088,0.001639141],"genre_scores_gemma":[0.9418734,0.0001652966,0.001789817,0.000003731211,0.00003372554,5.580884e-8,0.0006534297,0.00002198715,0.05545859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.471575,"threshold_uncertainty_score":0.9999307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08044903645788548,"score_gpt":0.2827493370594767,"score_spread":0.2023003006015912,"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."}}