{"id":"W3109171209","doi":"10.1002/aws2.1202","title":"An automated and high‐throughput method for adenosine triphosphate quantification","year":2020,"lang":"en","type":"article","venue":"AWWA Water Science","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adenosine triphosphate; Biomass (ecology); Water quality; Environmental science; Contamination; Throughput; Biochemical engineering; Microorganism; Computer science; Chemistry; Bacteria; Biology; Ecology; Engineering; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001630763,0.001151748,0.0006543766,0.002281737,0.0006083765,0.00105008,0.001367589,0.001902088,0.002199634],"category_scores_gemma":[0.001420341,0.0006666823,0.0006384079,0.001101334,0.0005312139,0.0009570514,0.0007966684,0.001734592,0.002056095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005744991,"about_ca_system_score_gemma":0.001024234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008064347,"about_ca_topic_score_gemma":0.001725158,"domain_scores_codex":[0.995272,0.0007565562,0.0002141249,0.0008561527,0.002771639,0.0001294772],"domain_scores_gemma":[0.9989045,0.0003388115,0.0001556927,0.0001200761,0.0004343858,0.00004660476],"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":[0.00006754483,0.0001963768,0.0008199071,0.0001861146,0.00004749341,0.00007603227,0.00005117833,0.0006763118,0.9623984,0.0004220484,0.001053532,0.03400495],"study_design_scores_gemma":[0.00004142465,0.0004710605,0.004923124,0.00004282346,0.00007994618,0.0005032532,0.00006090395,0.02928016,0.9509259,0.0005441402,0.01300847,0.0001188453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06238986,0.00235841,0.9248247,0.0003610607,0.0004790534,0.0009617484,0.001560828,0.003444731,0.003619552],"genre_scores_gemma":[0.287288,0.002215586,0.6960642,0.0005069035,0.0002691328,0.002729036,0.001965713,0.0001937851,0.008767654],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002281737,"threshold_uncertainty_score":0.008624434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02060539751320415,"score_gpt":0.2876949699401981,"score_spread":0.2670895724269939,"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."}}