{"id":"W3121866624","doi":"","title":"Treading Water: The Impact of High METRs on Working Families in Canada","year":2013,"lang":"en","type":"article","venue":"e-briefs","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Face (sociological concept); Business; Income Support; Low income; Working poor; Economic growth; Economics; Geography; Political science; Demographic economics; Sociology; Poverty; Social science; Law","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":[0.0001671152,0.00006468461,0.0001131511,0.00003967294,0.0001404,0.00003289301,0.0001985531,0.00002651497,0.0004181834],"category_scores_gemma":[0.00009516731,0.00003935928,0.00004075924,0.0002150045,0.0001046564,0.00007839121,0.00001390486,0.00008639892,0.00002297636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008210485,"about_ca_system_score_gemma":0.0006920869,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999612,"about_ca_topic_score_gemma":0.9995071,"domain_scores_codex":[0.9992089,0.00006328929,0.0001161839,0.0000910388,0.0001964898,0.0003241207],"domain_scores_gemma":[0.9996257,0.0001166074,0.00004587106,0.0001215433,0.00001459252,0.00007571615],"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":[0.00005089019,0.00006489427,0.123533,0.00001941538,0.0001384216,0.00004593252,0.1157132,0.002043142,0.00116422,0.05160653,0.554554,0.1510664],"study_design_scores_gemma":[0.0003527534,0.00005121882,0.8545057,0.0001011883,0.000006521598,7.8697e-7,0.005970067,0.00004915203,0.003127474,0.004139552,0.1314213,0.000274262],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772617,0.00003851101,4.801302e-7,0.005455684,0.00009853538,0.0001038752,0.00001780411,0.000004300555,0.01701912],"genre_scores_gemma":[0.996907,0.00002974545,0.000003712169,0.0007436135,0.0001086133,0.000007454606,8.100254e-7,0.000004934956,0.00219415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7309727,"threshold_uncertainty_score":0.4578815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01528198171153258,"score_gpt":0.2547673534685108,"score_spread":0.2394853717569782,"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."}}