{"id":"W7095003562","doi":"10.1007/978-3-031-97689-6_9","title":"Exploring the Nexus of Chemical Volatility and Soil Moisture in Soil Vapor Extraction for Industrial Pollutant Remediation—An Efficiency Analysis","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Volatility (finance); Pollutant; Water content; Moisture; Soil vapor extraction; Benzene; Xylene; Trace gas; Environmental remediation","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":[0.0004656933,0.0003353615,0.0004175036,0.0002556172,0.0001351671,0.000986368,0.0005756239,0.0004764541,0.002300424],"category_scores_gemma":[0.001130307,0.0003234232,0.000650443,0.0005566417,0.0003817547,0.001496961,0.0006054608,0.000574434,0.0003425225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004307825,"about_ca_system_score_gemma":0.0003558779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002114927,"about_ca_topic_score_gemma":0.004007059,"domain_scores_codex":[0.9998535,0.00005348314,0.000005411185,0.00002226617,0.00005036273,0.00001494096],"domain_scores_gemma":[0.999363,0.0005713119,0.00002200633,0.00002027272,0.00001937658,0.000003924315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002356315,0.000254177,0.01053588,0.0004619339,0.0002715168,0.0003584165,0.0001331072,0.5643823,0.05500278,0.1537403,0.002225044,0.2123989],"study_design_scores_gemma":[0.00000815113,0.0001255105,0.006094049,0.00002082578,0.00006353827,0.000117065,0.0001016054,0.9390108,0.01970634,0.03165043,0.003078976,0.00002265121],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4439504,0.01941863,0.4562462,0.002002851,0.00009557927,0.00008457652,0.0003813747,0.0003461238,0.07747415],"genre_scores_gemma":[0.9449586,0.006546578,0.02569874,0.00009280963,0.00005857071,0.00002799922,0.000151367,0.00009912736,0.02236617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002300424,"threshold_uncertainty_score":0.007695615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02757996555805928,"score_gpt":0.2244478554635293,"score_spread":0.1968678899054701,"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."}}