{"id":"W2154116076","doi":"10.1080/01490419.2014.902883","title":"Assessment of 3D Spatial Interpolation Methods for Study of the Marine Pelagic Environment","year":2014,"lang":"en","type":"article","venue":"Marine Geodesy","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pelagic zone; Kriging; Interpolation (computer graphics); Multivariate interpolation; Spatial analysis; Spatial variability; Geography; Computer science; Environmental science; Statistics; Mathematics; Oceanography; Remote sensing; Geology; Bilinear interpolation; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.009077519,0.0009612102,0.0005773418,0.001668816,0.0005790007,0.001135266,0.0009671416,0.0007936913,0.000826749],"category_scores_gemma":[0.01993466,0.0004263151,0.0009929314,0.001922057,0.0003527714,0.0007579658,0.001139215,0.0005818603,0.0002385783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007892622,"about_ca_system_score_gemma":0.001941588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01305172,"about_ca_topic_score_gemma":0.01691494,"domain_scores_codex":[0.9973282,0.001601943,0.0001725711,0.0001962239,0.0006373491,0.000063651],"domain_scores_gemma":[0.987444,0.007556604,0.0009634766,0.001321363,0.002523832,0.00019078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007034916,0.0002560082,0.0613442,0.0006212621,0.0004012197,0.000136418,0.0006143891,0.5345107,0.01709439,0.005334432,0.0008663193,0.3781172],"study_design_scores_gemma":[0.00002528606,0.00015682,0.009841491,0.00006331147,0.00004764547,0.00009014917,0.0001297306,0.9809877,0.006041712,0.001056661,0.001502655,0.000056831],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2822944,0.001262794,0.7115111,0.0003701301,0.00007847077,0.000253891,0.0007231077,0.001058753,0.002447355],"genre_scores_gemma":[0.413687,0.0005886704,0.584455,0.00003455701,0.00001415779,0.0002372054,0.0005170357,0.0001313571,0.0003350396],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01305172,"threshold_uncertainty_score":0.04800707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01344710886894128,"score_gpt":0.3029269590164079,"score_spread":0.2894798501474666,"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."}}