{"id":"W2335781254","doi":"","title":"Immigration to rural Canada; responding to labour market needs and promoting welcoming communities","year":2010,"lang":"en","type":"article","venue":"","topic":"Rural development and sustainability","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; Economic growth; Labour economics; Business; Political science; Economics","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":[0.001593503,0.0002384633,0.0002098267,0.0009720724,0.02413207,0.005010463,0.001664917,0.001904146,0.01563091],"category_scores_gemma":[0.00459994,0.0001539957,0.0002001169,0.001155839,0.003111161,0.001045294,0.004838969,0.00261655,0.0007421535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03228602,"about_ca_system_score_gemma":0.1819015,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9600673,"about_ca_topic_score_gemma":0.9914191,"domain_scores_codex":[0.9983566,0.000279063,0.00002136134,0.00005935114,0.0002008226,0.001082833],"domain_scores_gemma":[0.9928395,0.0003522624,0.000243972,0.00005250113,0.0009316287,0.005580206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003144736,0.001073312,0.1380965,0.0008394708,0.0000372093,0.005004804,0.1612693,0.0009126684,0.002912519,0.05296645,0.2255279,0.4110455],"study_design_scores_gemma":[0.0000533589,0.0001657813,0.09204886,0.0006415223,0.00002471293,0.0003324389,0.388999,0.0005280122,0.0005315029,0.004651762,0.5119462,0.00007682099],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6033444,0.004126715,0.0009274769,0.1378793,0.001487551,0.0003690332,0.0002911297,0.0001324754,0.2514419],"genre_scores_gemma":[0.8703672,0.003117582,0.001575339,0.009822289,0.0001709309,0.0001039696,0.0001106846,0.00004229675,0.1146898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03993273,"threshold_uncertainty_score":0.2342526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006848002337612612,"score_gpt":0.2007007205405416,"score_spread":0.193852718202929,"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."}}