{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065285,0.0001006183,0.0001534511,0.00002830512,0.0003327354,0.0001075169,0.0002068304,0.00005216008,0.000002055642],"category_scores_gemma":[0.0001219374,0.000103382,0.00004208928,0.0001938111,0.0000930897,0.0006507632,0.00003834677,0.00007798089,0.000001538566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004746436,"about_ca_system_score_gemma":0.0008620564,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9536629,"about_ca_topic_score_gemma":0.9008132,"domain_scores_codex":[0.9984514,0.00002297652,0.0003961366,0.0001379509,0.000675571,0.0003159838],"domain_scores_gemma":[0.9992711,0.00004906523,0.0002711446,0.0001558718,0.0001361966,0.0001166295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003033007,0.00007123428,0.7010799,0.00004901237,0.00006250814,0.00001319977,0.008258809,0.2472723,0.0000541402,0.04221421,0.00005373589,0.0008678668],"study_design_scores_gemma":[0.0002755385,0.00001882223,0.9865116,0.0001398143,0.000007731139,0.000001033689,0.01008438,0.0001892423,0.00003185592,0.001731431,0.0008269937,0.00018156],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.835618,0.00001377596,0.0001235616,0.0001587474,0.0002212972,0.0001086546,0.00001266716,0.00005091996,0.1636924],"genre_scores_gemma":[0.9990232,0.000003304054,0.0008197819,0.00004979243,0.00007735912,0.000004545268,0.000001888496,0.000004864376,0.00001527275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2854317,"threshold_uncertainty_score":0.4215797,"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."}}