{"id":"W7117450629","doi":"10.1002/hyp.70368","title":"Beyond Deuterium: <scp> δ <sup>18</sup> O </scp> Offsets From Cryogenic Vacuum Extraction Bias Water Source Apportionment in <scp> <i>Tamarix chinensis</i> </scp>","year":2025,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Science Foundation of Shandong Province; Key Technology Research and Development Program of Shandong; National Natural Science Foundation of China","keywords":"Tap water; Groundwater; Offset (computer science); Water extraction; Extraction (chemistry); Soil water; Apportionment; Water content","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":[0.0001645803,0.0002850411,0.0002037002,0.0001670187,0.0003053186,0.000330125,0.0002726837,0.0002771615,0.00113371],"category_scores_gemma":[0.0002921798,0.0001330891,0.0001722761,0.0002107329,0.0003805618,0.0003705199,0.0003132235,0.0004846439,0.0001675377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00041594,"about_ca_system_score_gemma":0.000258188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005623,"about_ca_topic_score_gemma":0.01051656,"domain_scores_codex":[0.999898,0.000007408161,0.000004152809,0.00004591218,0.00003056571,0.00001403673],"domain_scores_gemma":[0.9998611,0.00003430649,0.00002677731,0.00001314111,0.00005352013,0.00001106141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008069754,0.000004472791,0.003731479,0.00004504041,0.00001208894,0.00003813463,0.00006149112,0.00008594903,0.9935904,0.00004576889,0.00003854892,0.002266101],"study_design_scores_gemma":[0.00001004111,0.0001276073,0.08908118,0.00001403649,0.00005270017,0.0001280119,0.0002500719,0.002460774,0.9048269,0.0002663942,0.002759394,0.00002279956],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935246,0.0005027794,0.004143741,0.00008192853,0.00002490792,0.00002001293,0.0005069195,0.0000788307,0.001116365],"genre_scores_gemma":[0.9969332,0.000156291,0.001696638,0.00009900147,0.000005247666,0.00002828463,0.0003424158,0.00005346268,0.0006854337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005623,"threshold_uncertainty_score":0.01118058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01206931613602415,"score_gpt":0.2211167375095991,"score_spread":0.209047421373575,"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."}}