{"id":"W4299723080","doi":"10.1007/978-3-031-02120-6_4","title":"Terrain Maps","year":2018,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on games and computational intelligence","topic":"Rangeland Management and Livestock Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Terrain; Grid; Point (geometry); Computer science; Geography; Cartography; Computer graphics (images); Geodesy; Mathematics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001190179,0.000281915,0.000236081,0.00008671505,0.0001378368,0.00004815523,0.0002386876,0.0001680624,0.02055696],"category_scores_gemma":[0.00003640609,0.0002360858,0.00008642399,0.00002529152,0.0003809032,0.00004137212,0.0001543712,0.0001670947,0.001901565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005657212,"about_ca_system_score_gemma":0.000009033221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000177663,"about_ca_topic_score_gemma":0.00007173656,"domain_scores_codex":[0.9988068,0.00002524729,0.0002203775,0.000497241,0.0002565148,0.000193794],"domain_scores_gemma":[0.9992095,0.0004111876,0.0001248436,0.0001660565,0.00001179586,0.00007656935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001619641,0.00008774447,0.0002219749,0.00006258483,0.0002843968,0.00004646413,0.0007638091,0.02326732,0.0000101666,0.2014925,0.1890166,0.5845845],"study_design_scores_gemma":[0.0000343861,0.0002531558,0.001819672,0.00008870291,0.00005287722,0.00001390896,0.00002279331,0.001487222,0.0000642749,0.5356281,0.4600982,0.0004366178],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001092374,0.0002631197,0.01044039,0.0007934796,0.0002235564,0.0003482907,0.00003542582,0.00006522112,0.9867381],"genre_scores_gemma":[0.288156,0.0005126319,0.004521267,0.002762966,0.0005132295,0.00008417456,0.0000799028,0.0001058668,0.7032639],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5841479,"threshold_uncertainty_score":0.9988756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0128666229552856,"score_gpt":0.2269707727607578,"score_spread":0.2141041498054722,"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."}}