{"id":"W2330709470","doi":"10.1021/ac3033245","title":"In Vivo Solid-Phase Microextraction with in Vitro Calibration: Determination of Off-Flavor Components in Live Fish","year":2013,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Waterloo","funders":"University of Guelph","keywords":"Chemistry; Solid-phase microextraction; Chromatography; Fish <Actinopterygii>; Flavor; In vivo; In vitro; Phase (matter); Food science; Mass spectrometry; Gas chromatography–mass spectrometry; Biochemistry; Fishery; Organic chemistry; Biotechnology","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":[0.00001970557,0.0001190129,0.0002070771,0.0000629452,0.000005881807,0.000009490489,0.00009749822,0.000160626,0.0001052044],"category_scores_gemma":[0.00006821683,0.0001202427,0.00002236676,0.0002494693,0.00006661604,0.0002337721,0.00001886639,0.0002625236,0.000002987111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001797907,"about_ca_system_score_gemma":0.000004202047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005930229,"about_ca_topic_score_gemma":0.000031787,"domain_scores_codex":[0.9992359,0.000004816642,0.0003046685,0.000159645,0.0001043946,0.0001906171],"domain_scores_gemma":[0.9996909,0.00007056141,0.00003932166,0.0001384884,0.00002465962,0.00003603934],"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":[0.00003064705,0.0001078098,0.0004249058,0.00008480146,0.00000377969,0.00002319787,0.00002790856,0.0007815721,0.9973948,0.000001355735,0.00005087111,0.001068344],"study_design_scores_gemma":[0.0005578739,0.000008446568,0.0002446359,0.00004632742,0.000003496392,0.000004642031,0.00007675446,0.2019514,0.7968491,0.0001291646,0.00002627953,0.0001019546],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988136,0.00002097457,0.0004894828,0.0001371335,0.000008047789,0.0000934368,0.000008489843,0.00005939132,0.0003694138],"genre_scores_gemma":[0.999198,0.00001580635,0.0006527701,0.00001825711,0.00001330967,0.00002214339,0.00001827789,0.00001329202,0.00004816713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2011698,"threshold_uncertainty_score":0.4903356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0107577889206382,"score_gpt":0.2599442486984224,"score_spread":0.2491864597777842,"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."}}