{"id":"W2745077582","doi":"10.1145/3121113.3121232","title":"Building an historical GIS platform from archival data","year":2017,"lang":"en","type":"article","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Dalhousie University","keywords":"Directory; Census; Geographic information system; Geography; Ethnic group; Thematic map; Computer science; Nova scotia; Set (abstract data type); Scale (ratio); World Wide Web; Genealogy; Data science; Database; Regional science; Cartography; Archaeology; History; Sociology; Anthropology; Demography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007623968,0.00006663284,0.0001289744,0.00004750379,0.002574022,0.0003163804,0.001441389,0.00004077312,0.0001016063],"category_scores_gemma":[0.000385523,0.00005707413,0.00002788085,0.00003864645,0.000179031,0.001909743,0.0004496746,0.00007641545,0.00006880295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001161831,"about_ca_system_score_gemma":0.00004861179,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1463514,"about_ca_topic_score_gemma":0.02104311,"domain_scores_codex":[0.9989814,0.0000237412,0.0001926392,0.0001769898,0.0004019449,0.0002232568],"domain_scores_gemma":[0.99862,0.00008281024,0.0001542538,0.0009823643,0.00005327188,0.0001072376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001696872,0.00006108339,0.1348758,0.000009119845,0.0001068307,0.000006426918,0.05568061,0.000001332378,0.00005276129,0.6854426,0.04431729,0.07942919],"study_design_scores_gemma":[0.0002281422,0.00001776547,0.132527,0.00001287008,0.00001355203,4.502694e-7,0.007965594,0.0002861005,0.00000698895,0.01668672,0.8420473,0.000207521],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2702082,0.00004309275,0.0039824,0.00303625,0.00197626,0.0002064445,0.00005192822,0.0002058728,0.7202896],"genre_scores_gemma":[0.9900579,0.00002108824,0.007324418,0.00006534022,0.0005744446,0.000003945314,0.00001575432,0.000003779023,0.001933315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.79773,"threshold_uncertainty_score":0.9987245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1772506480609261,"score_gpt":0.3806854115351539,"score_spread":0.2034347634742278,"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."}}