{"id":"W6993014188","doi":"","title":"New Migration Management Policies in the Aftermath of Title 42","year":2023,"lang":"en","type":"other","venue":"Issue Lab (Candid)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Homeland security; Staffing; State (computer science); Population; Irregular migration; Border Security; Homeland; Representation (politics)","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00009512123,0.0001257925,0.000155609,0.0002645534,0.000008196326,0.00002010356,0.0002182468,0.00008142601,0.004469947],"category_scores_gemma":[0.000005510664,0.00009344717,0.00003528435,0.0003102956,0.00002169349,0.00001577052,0.00004009558,0.00007082571,0.02375305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000447354,"about_ca_system_score_gemma":0.00001816384,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.009593363,"about_ca_topic_score_gemma":0.02477277,"domain_scores_codex":[0.9993541,0.00003655961,0.0001240606,0.0001238962,0.0002264312,0.0001349602],"domain_scores_gemma":[0.9995291,0.00001351074,0.00009779034,0.0003354418,0.000005653527,0.00001845548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003461822,0.00001242187,0.000115206,0.00006269082,0.00003078073,0.00001145431,0.0007399098,0.000001250005,0.00001229193,0.001447104,0.9962989,0.001264499],"study_design_scores_gemma":[0.0001584697,0.000008580722,0.001576948,0.0001961562,0.00002992393,6.521595e-7,0.0001336792,0.000005235475,0.00002396284,0.0001413882,0.9976322,0.0000927706],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00006420265,0.0007746976,0.000009152211,0.0003554755,0.0001891903,0.0003166468,0.0001454761,0.0001953598,0.9979498],"genre_scores_gemma":[0.001002956,0.0002646249,0.0001481963,0.00008734181,0.0003421792,0.00002214618,0.00003811311,0.0005085039,0.997586],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01928311,"threshold_uncertainty_score":0.9970018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01242256225858434,"score_gpt":0.2770029244590415,"score_spread":0.2645803622004571,"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."}}