{"id":"W2079166477","doi":"10.1039/b806068a","title":"Fiber Bragg grating photoacoustic detector for liquid chromatography","year":2008,"lang":"en","type":"article","venue":"The Analyst","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Detection limit; Materials science; Repeatability; Fiber Bragg grating; Transducer; Photoacoustic effect; Detector; Optics; Laser; Chromatography; Chemistry; Acoustics","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":[0.00007857239,0.0001547352,0.0001875049,0.00008930281,0.0001921311,0.000012004,0.0001783326,0.0000490934,0.00007708529],"category_scores_gemma":[0.00003726995,0.0001179311,0.0001577314,0.0003659481,0.00006829321,0.00006640511,0.00001545631,0.0001136298,0.00004743981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002713495,"about_ca_system_score_gemma":0.000007509009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001064521,"about_ca_topic_score_gemma":0.00001772359,"domain_scores_codex":[0.99924,0.00001266428,0.0002010385,0.0001427172,0.0001213834,0.0002822136],"domain_scores_gemma":[0.9993283,0.0002010428,0.00003641983,0.0003421487,0.00003838064,0.00005375179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001289573,0.0000501282,0.0003251236,0.0002390895,0.001048329,0.00005761826,0.0029952,0.6589276,0.3257525,0.0001688454,0.008043921,0.002262712],"study_design_scores_gemma":[0.002043237,0.000477492,0.002373653,0.0001487081,0.0007721774,0.0004154829,0.0008830422,0.6954645,0.2553752,0.0005884664,0.03966959,0.001788468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9602237,0.0004351033,0.03728784,0.00002782415,0.0001234635,0.0002600598,0.00002317696,0.0003824371,0.001236378],"genre_scores_gemma":[0.9938853,0.0000383319,0.005428328,0.00005874265,0.0001573101,0.00005252147,0.000007288807,0.00005627306,0.0003158852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07037733,"threshold_uncertainty_score":0.480909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01398958291893982,"score_gpt":0.2197664078683965,"score_spread":0.2057768249494567,"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."}}