{"id":"W7099104376","doi":"","title":"Child Support in an Economic Downturn: Changes in Earnings, Child Support Orders, and Payments","year":2011,"lang":"en","type":"article","venue":"","topic":"Education, Technology, and Economics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Child support; Receipt; Poverty; Income Support; Quarter (Canadian coin); Public support; Earnings; Payment; Child poverty","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":[0.001284968,0.0002590226,0.0003724347,0.001439617,0.001085582,0.002501193,0.0005506594,0.001086857,0.003682067],"category_scores_gemma":[0.007363846,0.0001993469,0.0002964923,0.002681246,0.000520122,0.001290281,0.001805477,0.002221471,0.0007281851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002188767,"about_ca_system_score_gemma":0.0008441222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03068765,"about_ca_topic_score_gemma":0.04442672,"domain_scores_codex":[0.9990815,0.0001889795,0.00008307008,0.00007980106,0.0002085094,0.0003582081],"domain_scores_gemma":[0.9955194,0.0003904717,0.00249626,0.00007848469,0.0006045006,0.0009108573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003739705,0.0001628317,0.9734927,0.00003718823,0.00004967203,0.0005139881,0.001089178,0.0002173684,0.0001296743,0.0007518085,0.005027045,0.01815468],"study_design_scores_gemma":[0.000004136496,0.00002622016,0.9960396,0.00002715552,0.000007253991,0.0001072897,0.001922391,0.0001244648,0.00003078315,0.0001525213,0.001552529,0.000005736016],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868552,0.001836289,0.0001078744,0.003751655,0.0001373251,0.00002083604,0.001924178,0.00001078178,0.005355929],"genre_scores_gemma":[0.9963194,0.001267086,0.00007698473,0.0003079736,0.00009609749,0.00001586565,0.001240455,0.000004518564,0.0006716627],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03068765,"threshold_uncertainty_score":0.06101805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0208730679984185,"score_gpt":0.2390706281835288,"score_spread":0.2181975601851103,"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."}}