{"id":"W7095669619","doi":"","title":"Incidence, Entry and Exit Social Assistance Use in Canada: National and Provincial Trends in Incidence, Entry and Exit","year":2005,"lang":"en","type":"article","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Social assistance; Government (linguistics); Work (physics); Data collection","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":[0.0007633116,0.0005972753,0.0006786443,0.003762646,0.002667074,0.00239717,0.002242798,0.0009040853,0.003373039],"category_scores_gemma":[0.003542732,0.0006068878,0.001502116,0.006482042,0.0009593373,0.0009735345,0.002082288,0.001752707,0.0005143748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02522851,"about_ca_system_score_gemma":0.04476064,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9936463,"about_ca_topic_score_gemma":0.995203,"domain_scores_codex":[0.998073,0.00008425047,0.0001533266,0.00019809,0.0006431852,0.000848107],"domain_scores_gemma":[0.9926676,0.0002890041,0.001345938,0.0001476788,0.003354615,0.002195228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009236392,0.00003598927,0.9946374,0.00002940114,0.00003747042,0.00003799623,0.0005833953,0.0001209766,0.00008966418,0.00006125363,0.001165645,0.003108424],"study_design_scores_gemma":[0.00000312802,0.00001595232,0.9985701,0.00001652352,0.000009502653,0.00002343772,0.0007356255,0.0001618466,0.00002682265,0.000009283772,0.0004203314,0.000007492324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981813,0.0009520077,0.0001203228,0.0004032044,0.0000167853,0.00005390182,0.01441963,0.00005326145,0.002167956],"genre_scores_gemma":[0.9865997,0.0009139534,0.0001420103,0.00008348523,0.00001073381,0.00002614044,0.007669095,0.00001753705,0.004537438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02522851,"threshold_uncertainty_score":0.1830465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0163461267704063,"score_gpt":0.2758247674262567,"score_spread":0.2594786406558504,"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."}}