{"id":"W4236849532","doi":"10.32920/ryerson.14648850","title":"Refining field portable technology: quantification of arsenic field test kits","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Benchmark (surveying); Field (mathematics); Computer science; Calibration; Data mining; Process engineering; Biochemical engineering; Artificial intelligence; Statistics; Engineering; Mathematics; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003795121,0.000997791,0.0006029701,0.001406746,0.0004173663,0.002209423,0.001650378,0.001538882,0.003125035],"category_scores_gemma":[0.004856659,0.0005049972,0.0005667134,0.0009416259,0.0008843649,0.001434959,0.001108493,0.001264865,0.002844957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007696365,"about_ca_system_score_gemma":0.0007716587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009062492,"about_ca_topic_score_gemma":0.001393278,"domain_scores_codex":[0.9957954,0.0009762755,0.0001659158,0.0007081061,0.002198544,0.0001557569],"domain_scores_gemma":[0.9982458,0.0006096081,0.0001959169,0.000201741,0.0006990714,0.00004786357],"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":[0.0002589137,0.000196248,0.003550741,0.0009946078,0.00005253774,0.0001312607,0.0003348861,0.004440139,0.8219537,0.00408467,0.003245163,0.1607573],"study_design_scores_gemma":[0.00002496179,0.0009631645,0.003680712,0.0001811882,0.00006576387,0.0006289753,0.0002533477,0.01756835,0.9394852,0.002281712,0.03479363,0.00007298834],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1534151,0.002334883,0.8274832,0.0008529497,0.0005260266,0.0008912747,0.001162922,0.002902226,0.0104315],"genre_scores_gemma":[0.3140961,0.003847337,0.6597737,0.0005785471,0.0001217087,0.0009583847,0.001616282,0.0004027496,0.01860517],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003795121,"threshold_uncertainty_score":0.02007073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03013973061920595,"score_gpt":0.2798087825305945,"score_spread":0.2496690519113886,"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."}}