{"id":"W4213378855","doi":"10.2139/ssrn.4020076","title":"Detection and Monitoring of Cyanobacteria and Green Algae in River Water Using Derivative Spectrophotometry","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Cyanobacteria; Spectrophotometry; Algae; Environmental chemistry; Derivative (finance); Environmental science; Green algae; Chemistry; Botany; Chromatography; Biology; Bacteria; Business","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":[0.0003818985,0.0002495702,0.0002258675,0.0004917711,0.0002702095,0.0003583451,0.0003186207,0.0004536283,0.0004584265],"category_scores_gemma":[0.000487255,0.000196331,0.0001640468,0.0005323607,0.000307643,0.0003967331,0.0003511807,0.0004737572,0.0002175266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002924532,"about_ca_system_score_gemma":0.0003145927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00175535,"about_ca_topic_score_gemma":0.001961787,"domain_scores_codex":[0.9996386,0.00006163846,0.00001464619,0.00007031416,0.0001912951,0.00002361477],"domain_scores_gemma":[0.9997757,0.00007952227,0.00003226531,0.00001424128,0.00006794665,0.00003025553],"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":[0.0003488865,0.00007357128,0.0180648,0.00008594195,0.00002022115,0.0000489542,0.0001192996,0.0005025741,0.9605119,0.0002816703,0.0001898705,0.01975218],"study_design_scores_gemma":[0.00003705809,0.0006803843,0.06794313,0.00001605126,0.00006220728,0.0004775722,0.0002131645,0.01581488,0.910376,0.0005900017,0.0037473,0.00004238278],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9690754,0.001247197,0.02598232,0.0001141006,0.00002451272,0.00002366715,0.0002433796,0.0001680641,0.003121338],"genre_scores_gemma":[0.9757991,0.0007488223,0.02029414,0.0000755271,0.00001258229,0.00003546006,0.0002366372,0.00001750242,0.002780221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00175535,"threshold_uncertainty_score":0.003490269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01096349891440618,"score_gpt":0.2304158614931288,"score_spread":0.2194523625787227,"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."}}