{"id":"W2983517143","doi":"","title":"An Assessment of Global Digital Terrain Models Over Canada","year":2004,"lang":"en","type":"article","venue":"AGU Spring Meeting Abstracts","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Terrain; Digital elevation model; Computer science; Remote sensing; Geography; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001346096,0.0007253686,0.000539769,0.001709177,0.001877875,0.002990056,0.001470396,0.0006553745,0.002875488],"category_scores_gemma":[0.005648231,0.0003724516,0.0009057618,0.004964238,0.0007164078,0.001097672,0.000882611,0.0005758173,0.0003554408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03274388,"about_ca_system_score_gemma":0.01866999,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9891677,"about_ca_topic_score_gemma":0.9894081,"domain_scores_codex":[0.9992337,0.0001130822,0.00004631943,0.0001465151,0.0003359541,0.0001244945],"domain_scores_gemma":[0.9974483,0.0005154904,0.0001313755,0.0001754099,0.001546124,0.0001833007],"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":[0.0004156643,0.0001170056,0.08870773,0.0001556566,0.0001773775,0.0001399439,0.0003923712,0.8557342,0.0008359011,0.003196858,0.003655396,0.04647189],"study_design_scores_gemma":[0.0001287256,0.0000918763,0.1107777,0.0001098767,0.0001687746,0.00009068242,0.001849877,0.8706394,0.001168961,0.001338882,0.01352016,0.0001151618],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.96889,0.000667281,0.004362568,0.000970009,0.00005297562,0.0001111724,0.01011366,0.000564806,0.01426741],"genre_scores_gemma":[0.989574,0.0003967986,0.00405457,0.00004789951,0.000006212781,0.00002221068,0.004196514,0.00009211922,0.001609651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03274388,"threshold_uncertainty_score":0.2375746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0153604156936557,"score_gpt":0.3055354636863727,"score_spread":0.290175047992717,"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."}}