{"id":"W7042676433","doi":"","title":"Profile of census tracts in Lethbridge, Medicine Hat and Red Deer, 2006 Census : map volume","year":2009,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Volume (thermodynamics); Population; Field (mathematics); Population statistics","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":[0.0002154065,0.0005618907,0.000318059,0.003251856,0.0004582865,0.0006214621,0.0008382018,0.0002861177,0.07074097],"category_scores_gemma":[0.001491093,0.0005309223,0.0002251481,0.006263245,0.0001380179,0.0005962413,0.0006026562,0.0004597766,0.03922899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024,"about_ca_system_score_gemma":0.004176134,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2392865,"about_ca_topic_score_gemma":0.4426689,"domain_scores_codex":[0.9997469,0.00002348786,0.0000308612,0.00005083991,0.00009988603,0.00004801432],"domain_scores_gemma":[0.9991702,0.00005455132,0.0001455532,0.00004291577,0.000458068,0.0001286812],"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":[0.0001090873,0.00006042048,0.03495492,0.0004916214,0.00001908616,0.00008011379,0.0005353094,0.0003983138,0.0006724421,0.0004901309,0.9378265,0.02436214],"study_design_scores_gemma":[0.00003689434,0.00004165652,0.4656531,0.0002407866,0.00001536906,0.0001723857,0.0006984023,0.0005780758,0.000375058,0.0001009657,0.5320665,0.00002078932],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01715272,0.000405165,0.0004499483,0.0001522166,0.00006842586,0.0002500473,0.9515724,0.0004065471,0.02954252],"genre_scores_gemma":[0.02843247,0.00149997,0.003133358,0.0001515246,0.00003994149,0.0006237545,0.7863796,0.0002204087,0.1795189],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7607135,"threshold_uncertainty_score":0.4757875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00763374641730156,"score_gpt":0.2013241275167418,"score_spread":0.1936903810994402,"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."}}