{"id":"W2771467264","doi":"10.1111/cag.12430","title":"Environmental influences on skilled worker migration from Bangladesh to Canada","year":2017,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Blood Services","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Sanitation; Geography; Environmental planning; Socioeconomics; Immigration; Environmental protection; Business; Environmental science; Environmental engineering; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0003116073,0.0004128201,0.0003497594,0.001540748,0.005150515,0.0007268716,0.001049852,0.0002234721,0.0004081631],"category_scores_gemma":[0.0005039533,0.0004622425,0.0001709119,0.001096433,0.001300312,0.0005057568,0.00004786989,0.0002111153,0.00003216441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009092938,"about_ca_system_score_gemma":0.001058202,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.999769,"about_ca_topic_score_gemma":0.9999996,"domain_scores_codex":[0.9967808,0.0001453755,0.0004036913,0.0007165881,0.0006919471,0.001261634],"domain_scores_gemma":[0.9966876,0.0002341932,0.0002821904,0.0008843191,0.0001237534,0.001787971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005871367,0.00003804751,0.8989409,0.000008413885,0.0002030789,0.0001551665,0.02816848,0.00009314864,0.0001057609,0.006564918,0.03278249,0.03288091],"study_design_scores_gemma":[0.000215857,0.00005287283,0.6729597,0.00006086064,0.00003819184,0.000001274411,0.04141103,0.000009139402,0.00003256604,0.0005520272,0.284145,0.0005214558],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9768206,0.0003741194,0.00000138606,0.01391036,0.001611543,0.0006738578,0.001072613,0.000071991,0.005463541],"genre_scores_gemma":[0.9946242,0.000936583,0.0001072273,0.002513226,0.0005035811,0.0001484365,0.000295575,0.00004432856,0.0008268656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2513625,"threshold_uncertainty_score":0.9997829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02112484310073581,"score_gpt":0.2296918999970131,"score_spread":0.2085670568962773,"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."}}