{"id":"W2496127979","doi":"10.1002/ejic.201600606","title":"Multi‐Readout Logic Gate for the Selective Detection of Metal Ions at the Parts Per Billion Level","year":2016,"lang":"en","type":"article","venue":"European Journal of Inorganic Chemistry","topic":"Molecular Sensors and Ion Detection","field":"Chemistry","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Ontario Institute of Technology","keywords":"Metal ions in aqueous solution; Chemistry; Ligand (biochemistry); Ion; Metal; Stoichiometry; Molecule; Logic gate; Combinatorial chemistry; Nanotechnology; Inorganic chemistry; Physical chemistry; Materials science; Organic chemistry; Algorithm; Computer science","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":[0.0001825021,0.0002710822,0.0001802908,0.0002281114,0.0001980824,0.0006214668,0.0007324928,0.000339089,0.00163958],"category_scores_gemma":[0.0003999117,0.0001510837,0.0001357924,0.0002429577,0.0003515338,0.000584356,0.0003479404,0.0004910848,0.00036197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000464537,"about_ca_system_score_gemma":0.0003065729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003571431,"about_ca_topic_score_gemma":0.0007971773,"domain_scores_codex":[0.9998285,0.00002331256,0.00001244066,0.00003589266,0.00006867028,0.00003129969],"domain_scores_gemma":[0.9998652,0.00005177139,0.00002445922,0.00001596268,0.00002723991,0.00001536802],"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":[0.0003408487,0.00008525066,0.0003146678,0.0001784317,0.00001879531,0.0004465137,0.00007941115,0.004041576,0.9182963,0.02421417,0.001536333,0.05044768],"study_design_scores_gemma":[0.00004855182,0.000314613,0.0003550722,0.00001634754,0.00002606456,0.0004165556,0.00001682747,0.07728774,0.9058678,0.004237885,0.01137796,0.00003470557],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5559871,0.002189329,0.4071289,0.001239301,0.0005601134,0.000164606,0.000600766,0.003865309,0.02826458],"genre_scores_gemma":[0.9265179,0.0004139064,0.06761436,0.0003858769,0.00003646827,0.00005605558,0.0001474096,0.00004985953,0.004778132],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00163958,"threshold_uncertainty_score":0.005484939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02986498734575883,"score_gpt":0.2297682093339433,"score_spread":0.1999032219881845,"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."}}