{"id":"W2273009873","doi":"10.1016/j.chroma.2016.01.071","title":"A study of thin film solid phase microextraction methods for analysis of fluorinated benzoic acids in seawater","year":2016,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Chemistry; Chromatography; Solid-phase microextraction; Thermal desorption; Sample preparation; Detection limit; Extraction (chemistry); Desorption; Analyte; Derivatization; Solid phase extraction; Gas chromatography; Analytical Chemistry (journal); Mass spectrometry; Gas chromatography–mass spectrometry; Adsorption","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00171295,0.0002167148,0.00107034,0.000933606,0.00002667937,0.0000116192,0.0003254505,0.0001588942,0.0003490378],"category_scores_gemma":[0.0003879717,0.0001475633,0.0007444065,0.001318018,0.00008728225,0.0001627997,0.00004330527,0.0001989024,2.127672e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009357848,"about_ca_system_score_gemma":0.00008987414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000132897,"about_ca_topic_score_gemma":0.000009593561,"domain_scores_codex":[0.9973851,0.0001630883,0.001606828,0.0002324357,0.0003560646,0.0002564267],"domain_scores_gemma":[0.9970602,0.0007391453,0.001289072,0.0003090447,0.0004771669,0.0001253142],"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":[0.0006454227,0.002305076,0.03085761,0.0001953545,0.004630629,0.0000224711,0.0008139375,0.00006922633,0.9562465,0.000006124745,0.00003048701,0.004177186],"study_design_scores_gemma":[0.005524436,0.0003674915,0.006872585,0.0002151597,0.002075094,0.00002760457,0.001094846,0.0009566525,0.9821689,0.0003118778,0.0001982498,0.000187072],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9090213,0.000126622,0.0905014,0.00004467658,0.00004232788,0.0001009086,0.00002083667,0.000008769628,0.0001331787],"genre_scores_gemma":[0.9260928,0.00003330616,0.07375015,0.000005620149,0.00003087327,0.00001228339,0.000003828106,0.00001803073,0.00005311241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02592245,"threshold_uncertainty_score":0.6017458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04041348384185638,"score_gpt":0.416035486513827,"score_spread":0.3756220026719707,"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."}}