{"id":"W1574624437","doi":"10.1016/s1363-0814(05)80025-5","title":"Chapter 22 Applying a cybercartographic human interface (CHI) model to create a cybercartographic atlas of canada's trade with the world","year":2005,"lang":"en","type":"book-chapter","venue":"Modern cartography","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Atlas (anatomy); Interface (matter); Interface design; Computer science; Knowledge management; Relation (database); Control (management); Process management; Human–computer interaction; Engineering; Artificial intelligence; Data mining; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002005396,0.0006015985,0.0001861185,0.001022882,0.0017956,0.004187633,0.0008737218,0.0008057822,0.04175999],"category_scores_gemma":[0.0006953474,0.000230574,0.000424719,0.001542635,0.001171745,0.001505309,0.0007277615,0.0008402089,0.004538587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00721647,"about_ca_system_score_gemma":0.008888641,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4563668,"about_ca_topic_score_gemma":0.5554484,"domain_scores_codex":[0.9998577,0.0000144452,0.000003269916,0.00002470303,0.00007974897,0.0000202526],"domain_scores_gemma":[0.9998754,0.00002128987,0.000002679914,0.00001196798,0.00007452989,0.000014178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001805655,0.00005410664,0.001391519,0.0002266557,0.00001561863,0.0002216901,0.004407621,0.01283509,0.002091001,0.4625485,0.2384769,0.2777132],"study_design_scores_gemma":[0.00000426986,0.00001382513,0.001748664,0.0002020811,0.00001913166,0.0002042264,0.001414303,0.01356079,0.002041025,0.03922222,0.9415444,0.00002489007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006988877,0.002691522,0.1130426,0.002480042,0.00101166,0.0002373878,0.0009003625,0.001540574,0.8711069],"genre_scores_gemma":[0.1407265,0.005575133,0.1026066,0.0007534125,0.0001265103,0.0002351082,0.001331424,0.0008136882,0.7478316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5436332,"threshold_uncertainty_score":0.9074209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02094913406437008,"score_gpt":0.2516457635716234,"score_spread":0.2306966295072533,"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."}}