{"id":"W31871017","doi":"10.1136/jech-2019-213357","title":"Heuristics to Site Observers in a Terrain Represented by a Digital Elevation Matrix.","year":2010,"lang":"en","type":"article","venue":"Brazilian Symposium on GeoInformatics","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Canadian Institutes of Health Research; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canada Research Chairs","keywords":"Digital elevation model; Elevation (ballistics); Terrain; Heuristics; Computer science; Matrix (chemical analysis); Remote sensing; Geography; Mathematics; Cartography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003503281,0.000230614,0.0001999407,0.0003630846,0.00008997603,0.0009719051,0.00116068,0.00008712699,0.00001356197],"category_scores_gemma":[0.0001723719,0.0002282092,0.00005984562,0.0007573575,0.00003285251,0.002455547,0.000518692,0.0002548489,0.000585558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004838469,"about_ca_system_score_gemma":0.00003497804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003327751,"about_ca_topic_score_gemma":0.00004605737,"domain_scores_codex":[0.9981213,0.00001685804,0.0005830488,0.0003213646,0.0005063191,0.0004511326],"domain_scores_gemma":[0.9984385,0.0000789052,0.0001621092,0.001063705,0.00006204643,0.0001947147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000179664,0.001570508,0.0263185,0.0005723732,0.0001266419,0.000174367,0.01984174,0.005277494,0.007404874,0.1024103,0.6792303,0.1568933],"study_design_scores_gemma":[0.001648956,0.0003685222,0.006328513,0.00009645358,0.00001091909,0.00001813257,0.0002843152,0.705602,0.0006319919,0.0009053114,0.2831884,0.0009165097],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5905159,0.000009106431,0.3499705,0.01105478,0.00228294,0.002284136,0.0006305267,0.0009295932,0.04232259],"genre_scores_gemma":[0.8810139,0.00002135991,0.09986366,0.005243012,0.0002428296,0.0001044728,0.001311415,0.00006865402,0.01213069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7003245,"threshold_uncertainty_score":0.9372104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005176499113223808,"score_gpt":0.2362771326221698,"score_spread":0.231100633508946,"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."}}