{"id":"W2951671519","doi":"10.1002/chin.200718278","title":"Bioanalytical Applications of Solid‐Phase Microextraction","year":2007,"lang":"en","type":"article","venue":"ChemInform","topic":"Advanced Materials Characterization Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Chemistry; Solid-phase microextraction; Bioanalysis; Nanotechnology; Phase (matter); Chromatography; World Wide Web; Organic chemistry; Computer science; Gas chromatography–mass spectrometry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005809391,0.0007195295,0.0003734599,0.0008369329,0.0004843959,0.001118911,0.0003705906,0.0008134887,0.003250726],"category_scores_gemma":[0.0005594989,0.0002911285,0.0003368993,0.0004008638,0.0004259715,0.0003313854,0.0004369309,0.0008699719,0.002781279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004259883,"about_ca_system_score_gemma":0.0005643169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005757496,"about_ca_topic_score_gemma":0.00110008,"domain_scores_codex":[0.999496,0.0001114839,0.00001769539,0.0001036185,0.0002312909,0.0000398323],"domain_scores_gemma":[0.9996544,0.0001709624,0.00002595378,0.00002398479,0.00009310695,0.00003164154],"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":[0.0001006505,0.00004970926,0.0003181882,0.0001725349,0.00001606033,0.00007037062,0.00002368107,0.0001489838,0.9670935,0.0003390973,0.001039381,0.03062783],"study_design_scores_gemma":[0.000009427888,0.0001819987,0.001051551,0.00004541587,0.00002872248,0.0002793086,0.00003121896,0.000976069,0.9797049,0.0006780827,0.01700198,0.00001126773],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3693635,0.1520908,0.3777501,0.009834962,0.003631981,0.000920938,0.006643873,0.004263169,0.07550069],"genre_scores_gemma":[0.7455048,0.04058661,0.1754824,0.002308266,0.0005363084,0.0002487571,0.002253827,0.00015426,0.03292475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003250726,"threshold_uncertainty_score":0.01087475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0085352163079383,"score_gpt":0.2998002048998584,"score_spread":0.2912649885919201,"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."}}