{"id":"W2613246199","doi":"","title":"Subject Guides: ENPL 313: Rural Community Economic Development: Canadian Census Analyser","year":2010,"lang":"en","type":"libguides","venue":"","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Analyser; Subject (documents); Geography; Economic growth; Socioeconomics; Sociology; Economics; Demography; Library science; Population; Computer science","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":[0.002527441,0.001757226,0.001612684,0.01737122,0.008210412,0.006181013,0.002880996,0.00151216,0.2612103],"category_scores_gemma":[0.009836263,0.001044461,0.0006964194,0.04320528,0.00130958,0.00170766,0.001798934,0.001801629,0.07059948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07892632,"about_ca_system_score_gemma":0.1736986,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.993378,"about_ca_topic_score_gemma":0.993772,"domain_scores_codex":[0.9978417,0.0001409284,0.000182148,0.0001978387,0.001169938,0.0004674883],"domain_scores_gemma":[0.9874567,0.0009039703,0.0003591732,0.0003649355,0.010081,0.0008341774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001070042,0.000008175582,0.000599515,0.0001901579,0.000001940891,0.00001113495,0.0002620058,0.0001247982,0.00002559861,0.004480726,0.9803729,0.01391229],"study_design_scores_gemma":[0.000005623481,0.000002148176,0.008252415,0.0002102512,0.000004334518,0.00001427051,0.0005772537,0.0001387214,0.00008371188,0.0005734849,0.9901219,0.00001577839],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002249568,0.005460938,0.0007898068,0.006553723,0.001198155,0.001097228,0.5798314,0.001076934,0.4017422],"genre_scores_gemma":[0.01061358,0.008228034,0.002635322,0.0006449783,0.0003869244,0.0009221708,0.1493692,0.0008816215,0.8263182],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2612103,"threshold_uncertainty_score":0.8738356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02754578989933406,"score_gpt":0.2660848427443968,"score_spread":0.2385390528450627,"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."}}