{"id":"W7071162397","doi":"","title":"Profile of census tracts in Barrie, Belleville, Kingston, Oshawa and Peterborough : map volume","year":2009,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Volume (thermodynamics); Field (mathematics); Population","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":[0.0002248158,0.0005783618,0.0005631166,0.004246451,0.001205696,0.00128048,0.0009820005,0.0003923931,0.103267],"category_scores_gemma":[0.002183066,0.0005911058,0.0003209864,0.01260967,0.0003190058,0.0008703061,0.001017336,0.0005161706,0.0371774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001961855,"about_ca_system_score_gemma":0.008017403,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5769293,"about_ca_topic_score_gemma":0.8160239,"domain_scores_codex":[0.999589,0.00003130419,0.00003374946,0.00006207298,0.0001474265,0.000136461],"domain_scores_gemma":[0.9984657,0.0001237787,0.0001746357,0.00006421665,0.0009149237,0.0002568653],"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":[0.0001463051,0.00004060761,0.04746563,0.001057522,0.00002797457,0.0002977419,0.00358773,0.0004587969,0.001344024,0.001853961,0.8729796,0.0707401],"study_design_scores_gemma":[0.00001953016,0.00003223285,0.3260797,0.0002418143,0.00001523795,0.0003240659,0.005669977,0.000195822,0.0003797268,0.0001806261,0.6668117,0.00004960997],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.07925513,0.003625723,0.001604326,0.001305631,0.0003247708,0.0006970052,0.6936491,0.001428735,0.2181095],"genre_scores_gemma":[0.1366495,0.007154241,0.004680035,0.0004036753,0.00007046613,0.001015964,0.2844937,0.0008901716,0.5646423],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4230707,"threshold_uncertainty_score":0.8511244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005226729076831715,"score_gpt":0.1815410859750226,"score_spread":0.1763143568981909,"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."}}