{"id":"W4253285672","doi":"10.4095/300587","title":"Tactile Maps of Canada, Vancouver-Chinatown","year":2006,"lang":"en","type":"report","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chinatown; Geography; Cartography; Computer graphics (images); Computer science; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002339848,0.0007717079,0.0003017534,0.005137695,0.003177213,0.003657081,0.000739948,0.0003377371,0.1276852],"category_scores_gemma":[0.002445377,0.0002909209,0.0002228864,0.02082329,0.0005645967,0.000864294,0.00117479,0.0006384131,0.0197792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01434297,"about_ca_system_score_gemma":0.02691873,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9808499,"about_ca_topic_score_gemma":0.9914799,"domain_scores_codex":[0.999395,0.0000222011,0.00002166973,0.00006278003,0.0003787377,0.0001195695],"domain_scores_gemma":[0.9972077,0.00008681175,0.00004735843,0.00007040401,0.002309557,0.0002782244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006069362,0.00001160065,0.003953369,0.0003203636,0.000007401381,0.0001213384,0.00074931,0.0003054191,0.0002266438,0.002458182,0.9335321,0.05825363],"study_design_scores_gemma":[0.00001356706,0.000006339971,0.04431231,0.000197789,0.000006528086,0.0000840491,0.002619035,0.0002102002,0.0001429438,0.0004093616,0.9519664,0.00003140264],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01136773,0.001507648,0.001128336,0.001223367,0.0004962531,0.000286155,0.5416483,0.001549385,0.4407929],"genre_scores_gemma":[0.0868808,0.004554053,0.007044944,0.0005204396,0.00008605877,0.0005092634,0.3689646,0.0008641157,0.5305757],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1276852,"threshold_uncertainty_score":0.4271495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714931765588217,"score_gpt":0.2721449730088988,"score_spread":0.2549956553530166,"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."}}