{"id":"W2280536708","doi":"10.1021/acs.analchem.5b04661","title":"Cellulose-Based Biosensors for Esterase Detection","year":2016,"lang":"en","type":"letter","venue":"Analytical Chemistry","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Ministry of Technology, Innovation and Citizens' Services; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canada Foundation for Innovation","keywords":"Chemistry; Biosensor; Cellulose; Esterase; Chromatography; Biochemistry; Enzyme","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":[0.0006743714,0.0009638696,0.0004960225,0.0004448169,0.0003808698,0.0007985005,0.000959256,0.002313566,0.003134413],"category_scores_gemma":[0.0007248188,0.0003842818,0.0003561272,0.0004341541,0.0006797788,0.001057015,0.0005361036,0.002052474,0.003980485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001877366,"about_ca_system_score_gemma":0.0003999197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003718561,"about_ca_topic_score_gemma":0.0009772261,"domain_scores_codex":[0.9992356,0.0001281139,0.00003917013,0.0001418186,0.000378773,0.0000764176],"domain_scores_gemma":[0.9998499,0.00005004837,0.00001906304,0.00001578751,0.00003980182,0.00002534065],"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":[0.00005383233,0.00008183626,0.0001101441,0.0004841543,0.00001384052,0.0005181433,0.00006883613,0.0003008887,0.9433835,0.01566352,0.01017281,0.02914846],"study_design_scores_gemma":[0.00003442895,0.0001782399,0.000239294,0.00005356992,0.00001421902,0.001046826,0.00002860432,0.006701354,0.8619704,0.002170105,0.1275193,0.00004367928],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1326865,0.1491328,0.5451006,0.03438442,0.009542301,0.001335174,0.001960655,0.004581294,0.1212762],"genre_scores_gemma":[0.5430716,0.07610798,0.3061875,0.01256772,0.001828665,0.0009642986,0.001133108,0.0002131912,0.05792587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003134413,"threshold_uncertainty_score":0.01362133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107301949394209,"score_gpt":0.2071650172703332,"score_spread":0.1960919977763911,"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."}}