{"id":"W3100865577","doi":"10.3386/w28083","title":"Searching, Recalls, and Tightness: An Interim Report on the COVID Labor Market","year":2020,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Banca d'Italia; Canada Research Chairs","keywords":"Interim; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Virology; Political science; Medicine; Law; Outbreak","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01962043,0.0003520989,0.000938747,0.001141479,0.0002663494,0.0002649865,0.001054782,0.0004807852,0.003058316],"category_scores_gemma":[0.01826591,0.0003292089,0.000192819,0.0003331593,0.0005179491,0.0002962342,0.0004939572,0.001701576,0.0003835358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002652667,"about_ca_system_score_gemma":0.004004797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003562576,"about_ca_topic_score_gemma":0.0002914881,"domain_scores_codex":[0.9955297,0.000311492,0.001612566,0.00128879,0.0006645274,0.0005929969],"domain_scores_gemma":[0.9939629,0.003017316,0.001066166,0.0008883257,0.0006749093,0.0003903126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000222146,0.0001344306,0.01301461,0.0003850326,0.0003518911,0.00005758161,0.000337996,0.00007806399,0.0000166018,0.6274704,0.3572024,0.0007288353],"study_design_scores_gemma":[0.0004006273,0.0002918509,0.007013897,0.0001044264,0.000006950208,0.0001053622,0.00005169011,0.001366611,0.0000245618,0.3161367,0.6741397,0.0003576121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01277293,0.001271626,0.00002124081,0.02447075,0.0008644974,0.001163335,0.001282773,0.00004564948,0.9581072],"genre_scores_gemma":[0.950588,0.005099545,0.0001758858,0.001805255,0.002218476,0.0002382543,0.0008961807,0.0001829648,0.03879538],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9378151,"threshold_uncertainty_score":0.999916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5002564371071142,"score_gpt":0.5098411128994328,"score_spread":0.009584675792318587,"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."}}