{"id":"W7055138362","doi":"","title":"Assessing Point of Use Water Treatment Technologies under Real-Use Conditions: The Field Challenge Test Technique","year":2023,"lang":"en","type":"dissertation","venue":"UVic’s Research and Learning Repository (University of Victoria)","topic":"Laser Design and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Log reduction; Field (mathematics); Test (biology); Sample (material); Water treatment; Work (physics); Measure (data warehouse)","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":[0.004380313,0.001178426,0.0008133248,0.000844448,0.0009113997,0.001598843,0.001696238,0.001930401,0.00215646],"category_scores_gemma":[0.00561647,0.0005586644,0.0007970693,0.0008775715,0.001340704,0.001403491,0.002005229,0.001478077,0.001051491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104704,"about_ca_system_score_gemma":0.001411589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005399527,"about_ca_topic_score_gemma":0.0104155,"domain_scores_codex":[0.9923494,0.002152345,0.0004440378,0.001212254,0.003442591,0.0003994033],"domain_scores_gemma":[0.9952728,0.001201896,0.0008738934,0.0005264663,0.001971495,0.0001533865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005878819,0.001440192,0.03090118,0.001141074,0.0001080895,0.0002049739,0.001079418,0.001581072,0.9195451,0.0007483291,0.001925624,0.04073706],"study_design_scores_gemma":[0.0001066874,0.01371391,0.05072725,0.0002028166,0.0001839611,0.0005912866,0.002207612,0.007315596,0.9021968,0.0009793597,0.02157631,0.0001984955],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7399409,0.001579752,0.227284,0.001255963,0.000589178,0.009893436,0.004648253,0.0007653838,0.01404308],"genre_scores_gemma":[0.6984233,0.002477345,0.2696216,0.001430944,0.0001333125,0.01093485,0.003235646,0.0001973096,0.01354574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005399527,"threshold_uncertainty_score":0.02316558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04611498543267897,"score_gpt":0.3031387846486376,"score_spread":0.2570237992159586,"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."}}