{"id":"W2076754033","doi":"10.1016/j.talanta.2003.11.035","title":"Headspace single-drop microextration for the detection of organotin compounds","year":2004,"lang":"en","type":"article","venue":"Talanta","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":104,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"Agilent Technologies","keywords":"Chemistry; Tributyltin; Chromatography; Mass spectrometry; Solid-phase microextraction; Certified reference materials; Drop (telecommunication); Solvent; Detection limit; Solvent extraction; Analytical Chemistry (journal); Sample preparation; Gas chromatography; Gas chromatography–mass spectrometry; Extraction (chemistry); Environmental chemistry; Organic chemistry","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":[0.0001350727,0.00009794369,0.0001213655,0.00001149425,0.00007752551,0.00001648606,0.0001329801,0.00007460463,0.00007900311],"category_scores_gemma":[0.0001296075,0.00007636751,0.00005943809,0.00008580525,0.00007112621,0.00002866956,0.00002736928,0.00008823426,0.000005877394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001369773,"about_ca_system_score_gemma":0.00004127814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003468477,"about_ca_topic_score_gemma":0.00004024077,"domain_scores_codex":[0.9993687,0.000006673682,0.0001998722,0.000152342,0.0001275341,0.0001448389],"domain_scores_gemma":[0.9994119,0.0001939576,0.00009570877,0.0001983332,0.00006593791,0.00003413483],"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":[0.00004073965,0.00005353986,0.00009056641,0.00009078889,0.00002823772,6.026325e-7,0.0001122099,0.0000169746,0.9982197,0.00006698838,0.00005329836,0.001226373],"study_design_scores_gemma":[0.0004319883,0.00001708857,0.00006867093,0.00002978457,0.00003686464,0.00002120573,0.0001480687,0.0001978101,0.9934357,0.0004298498,0.005091158,0.00009174415],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4443769,0.0002119708,0.5481878,0.001432883,0.0001074219,0.0001756017,0.00002657179,0.0001033449,0.005377535],"genre_scores_gemma":[0.9938952,0.000006890817,0.005269443,0.00005452832,0.00008994208,0.00001181562,0.0000201199,0.0000156737,0.0006363264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5495183,"threshold_uncertainty_score":0.3114176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03032979192680414,"score_gpt":0.2767878060224989,"score_spread":0.2464580140956947,"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."}}