{"id":"W4253237694","doi":"10.32920/ryerson.14663859","title":"Cosmopolitan county: migrant farm workers' impact on the agricultural community of Leamington","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Agriculture and Farm Safety","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Toronto Metropolitan University","funders":"","keywords":"Agriculture; Invisibility; Farm workers; Interview; Migrant workers; Visibility; Political science; Economic growth; Demographic economics; Socioeconomics; Geography; Sociology; Economics; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003636807,0.000117943,0.0001513381,0.0004701499,0.005768636,0.001245088,0.0005487412,0.0003996123,0.004922786],"category_scores_gemma":[0.001050665,0.00008699971,0.00008138153,0.0004968927,0.001536707,0.0005585265,0.002697346,0.0004215789,0.0001860831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003121484,"about_ca_system_score_gemma":0.003239325,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4595637,"about_ca_topic_score_gemma":0.7994621,"domain_scores_codex":[0.9996713,0.0001212613,0.000008987469,0.00003813078,0.00003294064,0.0001274415],"domain_scores_gemma":[0.9991203,0.0001380271,0.0001520222,0.00003189892,0.0001333115,0.0004245232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000179861,0.0002007922,0.5236014,0.0001046046,0.00001917717,0.007347186,0.4339095,0.00007386257,0.002528793,0.0008758792,0.003762579,0.02739644],"study_design_scores_gemma":[0.000004052886,0.00007229024,0.4156178,0.00004214301,0.000006656518,0.0003914553,0.5754727,0.00003177898,0.0001063896,0.00007241181,0.008172383,0.000009868959],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971209,0.00004968618,0.000008967413,0.0002510895,0.000004687522,0.000007198238,0.00002619177,0.000001244405,0.00253009],"genre_scores_gemma":[0.9972766,0.0001011017,0.00003879128,0.0001112462,0.000003553869,0.000008961085,0.00002422739,0.000001574678,0.002433978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5404363,"threshold_uncertainty_score":0.9137775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02863278566538826,"score_gpt":0.2464956258063782,"score_spread":0.21786284014099,"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."}}