{"id":"W2278299854","doi":"10.1007/978-94-007-4153-9_42","title":"Interpolation of Concentration Measurements by Kriging Using Flow Coordinates","year":2012,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Curvilinear coordinates; Kriging; Interpolation (computer graphics); Coordinate system; Cartesian coordinate system; Hydraulic head; Spatial reference system; Flow (mathematics); Plume; Orthogonal coordinates; Discretization; Stream function; Transformation (genetics); Advection; Nonlinear system; Geology; Mathematics; Computer science; Geometry; Mathematical analysis; Geotechnical engineering; Mechanics; Geography; Remote sensing; Statistics; Physics; Chemistry; Meteorology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002914623,0.000265573,0.0003628317,0.00004509938,0.0001455534,0.00001370075,0.0000830175,0.0002074978,0.001191872],"category_scores_gemma":[0.000154177,0.0002799842,0.00003337735,0.00003192358,0.0006779972,0.0001144647,0.0001055227,0.0001960708,0.00005855973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005451314,"about_ca_system_score_gemma":0.00002078544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003178524,"about_ca_topic_score_gemma":0.00008486336,"domain_scores_codex":[0.9987188,0.0000563908,0.0004241516,0.0003032575,0.0002273012,0.0002700803],"domain_scores_gemma":[0.9989117,0.0003300871,0.0004918067,0.0001230224,0.00005953981,0.00008383455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002638863,0.0001374492,0.07898227,0.0003542894,0.0006666325,0.00002204216,0.004111392,0.001071407,0.007811002,0.8071087,0.01936923,0.08010171],"study_design_scores_gemma":[0.003401845,0.001710237,0.01689173,0.00100668,0.001785324,0.00008860068,0.000979791,0.4577514,0.0009255257,0.4145269,0.09754042,0.003391568],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01343268,0.006803092,0.7873005,0.0001311595,0.001278376,0.001097283,0.001956487,0.00005991009,0.1879405],"genre_scores_gemma":[0.6346634,0.001666081,0.3261134,0.0004034335,0.0001223961,0.00001720101,0.002437546,0.0001512812,0.03442528],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6212307,"threshold_uncertainty_score":0.9999653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04756708123971831,"score_gpt":0.2817556148915185,"score_spread":0.2341885336518002,"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."}}