{"id":"W1968014753","doi":"10.1023/b:supe.0000020178.66165.f3","title":"Optimization of DTM Interpolation Using SFS with Single Satellite Imagery","year":2004,"lang":"en","type":"article","venue":"The Journal of Supercomputing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Interpolation (computer graphics); Terrain; Remote sensing; Computation; Digital elevation model; Satellite; Context (archaeology); Computer vision; Artificial intelligence; Field (mathematics); Elevation (ballistics); Computer graphics (images); Algorithm; Geology; Image (mathematics); Geography; Cartography","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":[0.0007536573,0.0007241274,0.0007617369,0.0008870859,0.0005438658,0.0005397347,0.0007345169,0.0008623821,0.004274106],"category_scores_gemma":[0.003338963,0.000596179,0.0008559434,0.001577125,0.0004046595,0.0008453831,0.0005124911,0.0007091704,0.0008386511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007933541,"about_ca_system_score_gemma":0.001911395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02569518,"about_ca_topic_score_gemma":0.02621689,"domain_scores_codex":[0.999757,0.00007387706,0.00001807623,0.00005434256,0.00006544346,0.00003126106],"domain_scores_gemma":[0.9990858,0.0004909324,0.0000586336,0.0001336059,0.0001929557,0.00003813593],"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":[0.0001708544,0.0000569768,0.001092109,0.0000665242,0.000034517,0.00003756596,0.00004808738,0.8782427,0.004552132,0.002512471,0.001452117,0.111734],"study_design_scores_gemma":[0.000007070161,0.000009013814,0.0001735968,0.000001807431,0.000002719198,0.000005067114,0.000004124692,0.9982777,0.0007660475,0.0004274929,0.0003224997,0.000002784951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1419753,0.0002505558,0.8508092,0.0002186938,0.0001593865,0.00006712427,0.00056651,0.00204695,0.003906379],"genre_scores_gemma":[0.4724522,0.0001048924,0.5234966,0.00005299801,0.00005930952,0.0000858587,0.0007790028,0.0004917891,0.00247738],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02569518,"threshold_uncertainty_score":0.05109125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0159004112065297,"score_gpt":0.2238392353639511,"score_spread":0.2079388241574213,"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."}}