{"id":"W4247477702","doi":"10.4095/301067","title":"Labour Force Occupation, 2001 - Natural and Applied Sciences and Related Occupations (by census subdivision)","year":2010,"lang":"en","type":"report","venue":"","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subdivision; Census; Natural (archaeology); Geography; Demographic economics; Genealogy; Demography; Sociology; History; Economics; Population; Archaeology","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":[0.0005905646,0.001163554,0.0004205461,0.005636892,0.002967165,0.001423547,0.001463412,0.0006359415,0.01180457],"category_scores_gemma":[0.002380095,0.0005604268,0.0006254459,0.01038282,0.0003082443,0.0007605583,0.0009731937,0.001222082,0.005528659],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02263762,"about_ca_system_score_gemma":0.04620601,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9907463,"about_ca_topic_score_gemma":0.9946263,"domain_scores_codex":[0.998841,0.00002735756,0.00007052014,0.0000711057,0.0007231771,0.0002669725],"domain_scores_gemma":[0.9974788,0.00004553274,0.0001268659,0.00003844024,0.002038736,0.0002716457],"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":[0.0001247522,0.0001353811,0.08339699,0.0007287994,0.00004927079,0.0001276277,0.000884932,0.0005294852,0.0002715314,0.0008444801,0.8843635,0.0285433],"study_design_scores_gemma":[0.00004869584,0.0000387402,0.7893955,0.0004146989,0.00003487923,0.0001107236,0.00179377,0.0004009968,0.0002395252,0.0001161422,0.207375,0.00003134893],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02156383,0.001605679,0.0001435423,0.0008565679,0.0002581759,0.0004364663,0.9481999,0.0001314923,0.02680428],"genre_scores_gemma":[0.06688459,0.006590818,0.001172916,0.0005349004,0.00009166195,0.0006750822,0.8353315,0.00006041223,0.08865806],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9773624,"threshold_uncertainty_score":0.1642482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881063219737726,"score_gpt":0.2952111375276907,"score_spread":0.2764005053303135,"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."}}