{"id":"W1969700024","doi":"10.3141/1977-15","title":"Nonstationary Spatial Interpolation Method for Urban Model Development","year":2006,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Interpolation (computer graphics); Transport engineering; Multivariate interpolation; Computer science; Econometrics; Geography; Engineering; Mathematics; Bilinear interpolation; Statistics; Telecommunications","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":[0.002989177,0.0002502746,0.0003461098,0.0008587659,0.0006034111,0.000101256,0.0007687935,0.0001907598,0.0000650318],"category_scores_gemma":[0.00006477286,0.0002161893,0.0002860397,0.001036835,0.0001996714,0.0004482849,0.000005341946,0.00119477,0.00001341138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003490917,"about_ca_system_score_gemma":0.0006047926,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003841752,"about_ca_topic_score_gemma":0.03452235,"domain_scores_codex":[0.9949527,0.0002899785,0.001570032,0.0003293824,0.002144935,0.0007129133],"domain_scores_gemma":[0.995112,0.0008831696,0.0002587918,0.0003624662,0.003182529,0.0002010473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005661781,0.0002619584,0.0200116,0.0003802032,0.0001592071,0.000007706494,0.002696987,0.9088411,0.01527384,0.008597009,0.02441506,0.01878916],"study_design_scores_gemma":[0.001646043,0.0002050177,0.2099036,0.0002492212,0.00006506294,4.711006e-7,0.0004291011,0.7443646,0.006380978,0.01991536,0.01647275,0.0003677259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.246391,0.000100858,0.7510334,0.0006881351,0.0002953034,0.001135247,0.0001006145,0.00006660482,0.000188893],"genre_scores_gemma":[0.752701,0.00006315966,0.2460711,0.00001729826,0.0002608214,0.0003568366,0.000115139,0.00007780965,0.000336805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5063101,"threshold_uncertainty_score":0.9830951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06643942650234634,"score_gpt":0.3676065398381993,"score_spread":0.3011671133358529,"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."}}