{"id":"W2109750803","doi":"10.3390/s131114714","title":"A Microfluidic Bioreactor with in Situ SERS Imaging for the Study of Controlled Flow Patterns of Biofilm Precursor Materials","year":2013,"lang":"en","type":"article","venue":"Sensors","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Université Laval","keywords":"Biofilm; Microfluidics; Bioreactor; In situ; Materials science; Nanotechnology; Microchannel; Raman spectroscopy; Surface-enhanced Raman spectroscopy; Chemistry; Raman scattering; Optics","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":[0.0006082499,0.0009780588,0.0007491983,0.0004117174,0.0004004902,0.0004994139,0.001137517,0.0009032773,0.0005658436],"category_scores_gemma":[0.0005028532,0.0004656985,0.0004316109,0.0002606167,0.0003668267,0.0004448576,0.0005952751,0.0005743716,0.0004251565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007906774,"about_ca_system_score_gemma":0.0009090885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007057838,"about_ca_topic_score_gemma":0.001123805,"domain_scores_codex":[0.99959,0.00004840477,0.0000284472,0.0001271771,0.0001550552,0.00005091018],"domain_scores_gemma":[0.9996223,0.0001002577,0.000105574,0.00003346042,0.00006882894,0.00006949167],"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":[0.00002174728,0.00001452703,0.00009688767,0.00004462521,0.000002911314,0.00002553784,0.000007559503,0.00008103873,0.9969648,0.0001130741,0.0001053538,0.002522075],"study_design_scores_gemma":[0.0000264227,0.0003043795,0.001825668,0.000009657113,0.00002659737,0.000499298,0.00001042451,0.005606399,0.9848622,0.000103983,0.006695331,0.00002959273],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4898629,0.01191388,0.4871409,0.001283054,0.0009552995,0.0006236038,0.001445595,0.003758614,0.003016283],"genre_scores_gemma":[0.4896287,0.003219976,0.5019563,0.0004343526,0.0002147675,0.0006505821,0.0007068882,0.0001056431,0.003082804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001137517,"threshold_uncertainty_score":0.005736768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008643121188046377,"score_gpt":0.2216936612270695,"score_spread":0.2130505400390231,"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."}}