{"id":"W2025505307","doi":"10.1080/01615440009598961","title":"Reconstructing the Geographical Framework of the 1901 Census of Canada","year":2000,"lang":"en","type":"article","venue":"Historical Methods A Journal of Quantitative and Interdisciplinary History","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Census; Geography; Regional science; Cartography; Economic geography; Demography; Population; Sociology","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":[0.0003210424,0.0005043616,0.0002738517,0.007788573,0.002008893,0.00276705,0.001087386,0.0003613642,0.03037227],"category_scores_gemma":[0.004115222,0.0003828231,0.0006396527,0.01696752,0.0007414473,0.0007594831,0.001295439,0.0008220264,0.002723726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01382659,"about_ca_system_score_gemma":0.03258761,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9888151,"about_ca_topic_score_gemma":0.9935547,"domain_scores_codex":[0.9995653,0.00004132252,0.0000174212,0.00009114311,0.0001638701,0.0001210392],"domain_scores_gemma":[0.9991857,0.0001114883,0.00006158669,0.00009020107,0.000476758,0.00007416817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002034772,0.00009141062,0.09177578,0.0008480121,0.0001340348,0.0004331103,0.007476187,0.04824354,0.001521705,0.133622,0.3258849,0.3897659],"study_design_scores_gemma":[0.00006181029,0.00002250339,0.2080479,0.0006427351,0.00007571413,0.0002291479,0.01095431,0.02281076,0.001008432,0.01193985,0.7440821,0.0001248177],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.2104902,0.004193915,0.05402448,0.004742234,0.0006628897,0.0009658777,0.3956007,0.005611781,0.323708],"genre_scores_gemma":[0.6997986,0.005605705,0.1087582,0.0002177695,0.00006844748,0.0004698254,0.1390258,0.001344217,0.04471143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03037227,"threshold_uncertainty_score":0.1016054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08129797304084609,"score_gpt":0.4278889291966627,"score_spread":0.3465909561558166,"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."}}