{"id":"W6922548737","doi":"10.13140/rg.2.2.12549.14569","title":"Investigating Rural Precarious Employment in Ontario","year":2017,"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":"Work (physics); Government (linguistics); Unemployment; Agency (philosophy)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001834846,0.00007772299,0.00009602055,0.000003774295,0.000330205,0.0001574295,0.0002697768,0.00004329247,0.0004673957],"category_scores_gemma":[0.00007190082,0.00002521287,0.00003193411,0.00002897562,0.00005501685,0.0001982298,0.0001361926,0.00009865114,0.00001750999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001360727,"about_ca_system_score_gemma":0.00002598946,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3923416,"about_ca_topic_score_gemma":0.9020973,"domain_scores_codex":[0.9993737,0.0000190334,0.0001431842,0.0001396754,0.0001096226,0.0002147554],"domain_scores_gemma":[0.9997702,0.0000277214,0.00005099349,0.00006540953,0.00002399621,0.00006171537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001821116,0.00001576133,0.9686982,7.607358e-7,0.000001353386,0.000001770083,0.000299774,3.95296e-7,0.002669965,0.0002134041,0.0001994954,0.02789729],"study_design_scores_gemma":[0.00007590791,0.00003227219,0.9904114,0.000008461737,6.974396e-7,4.79182e-7,0.0002373716,0.000007366574,0.000467995,0.003876251,0.004785707,0.00009609937],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810958,0.000006211354,9.859167e-8,0.002853311,0.00007619083,0.0001514728,3.580276e-7,0.00002748803,0.0157891],"genre_scores_gemma":[0.9894435,0.000001078717,0.0001100717,0.00012176,0.00002394107,0.00001184625,0.000007064107,2.049926e-7,0.0102805],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5097558,"threshold_uncertainty_score":0.6117049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03186219347482425,"score_gpt":0.2373353813857348,"score_spread":0.2054731879109106,"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."}}