{"id":"W2055912506","doi":"10.1021/es301686k","title":"Selection, Characterization, and Biosensing Application of High Affinity Congener-Specific Microcystin-Targeting Aptamers","year":2012,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":132,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aptamer; Congener; Microcystin; Detection limit; Biosensor; Chemistry; Combinatorial chemistry; Biology; Environmental chemistry; Chromatography; Biochemistry; Molecular biology; Cyanobacteria; Genetics; Bacteria","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002346219,0.0001114163,0.0001160148,0.0001772949,0.0002082118,0.000008385979,0.0001229063,0.0001280178,0.000001638882],"category_scores_gemma":[0.00002528784,0.0001072276,0.0000217697,0.0004320323,0.001224401,0.00001742742,0.0001478934,0.00006726212,0.0000019148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004187813,"about_ca_system_score_gemma":0.00001007633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000421868,"about_ca_topic_score_gemma":0.000001736859,"domain_scores_codex":[0.9991111,0.00001650166,0.0001834706,0.0003255141,0.0001095583,0.0002538769],"domain_scores_gemma":[0.9995812,0.000003572821,0.0001616346,0.000179663,0.00002134125,0.00005255836],"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":[0.000006028325,0.00004064599,0.023219,0.000001325089,0.000005150106,6.407551e-8,0.00001373175,9.811559e-7,0.9465332,0.00005581826,0.000006975776,0.03011707],"study_design_scores_gemma":[0.00007140765,0.00005846244,0.02129928,0.000002584727,0.000008275777,0.00002296492,0.00008147983,0.00002887507,0.9719667,0.00002709652,0.006313935,0.0001189614],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879855,0.000204913,0.01148348,0.0001182524,0.00003603363,0.000105423,0.00001122802,0.00003939613,0.00001579123],"genre_scores_gemma":[0.9872587,0.0003736783,0.01217019,0.00003794776,0.00005625207,0.00000411703,0.0000678748,0.000008773107,0.000022423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02999811,"threshold_uncertainty_score":0.4511357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003839888102664158,"score_gpt":0.2109649234123962,"score_spread":0.207125035309732,"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."}}