{"id":"W1536561502","doi":"10.1002/9781118801628.ch08","title":"Visualizing Scale‐Domain Manifolds: A Multiscale Geo‐Object‐Based Approach","year":2014,"lang":"en","type":"other","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Scale (ratio); Domain (mathematical analysis); Computer science; Object (grammar); Computer graphics (images); Geology; Artificial intelligence; Mathematics; Geography; Cartography; Mathematical analysis","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003716277,0.0004199273,0.0004787059,0.0005100241,0.00009191514,0.0004234235,0.001594344,0.0003267682,0.001076203],"category_scores_gemma":[0.00002117916,0.0003698889,0.0001614645,0.0005278387,0.00007207846,0.0001393183,0.0003780855,0.0001722148,0.001063199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003899457,"about_ca_system_score_gemma":0.00008716462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001630548,"about_ca_topic_score_gemma":0.000136817,"domain_scores_codex":[0.9975676,0.0001605335,0.0003665118,0.0008986584,0.0005604163,0.0004462835],"domain_scores_gemma":[0.9981338,0.00004321353,0.0002712683,0.001302041,0.00004427436,0.000205387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001246179,0.0002266946,0.00006742209,0.0001910101,0.00004368703,0.000008296425,0.00007876685,0.00003288751,0.00002595352,0.08740034,0.9096351,0.002288621],"study_design_scores_gemma":[0.0004528109,0.0000262793,0.00001210265,0.0001081149,0.00001492087,0.000005492968,0.00002882866,0.3057166,0.00004374525,0.0001344819,0.6929716,0.0004850562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[3.962321e-7,0.0000479722,0.5573611,0.00005220481,0.000153861,0.0001612271,0.00001660767,0.000686212,0.4415204],"genre_scores_gemma":[0.0003423216,0.00001828501,0.333017,0.00239629,0.0003477208,0.00002703261,0.0003158127,0.0003406799,0.6631948],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.3056837,"threshold_uncertainty_score":0.9998753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01727988014524109,"score_gpt":0.2800799103045402,"score_spread":0.2628000301592991,"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."}}