{"id":"W6929901462","doi":"10.5281/zenodo.10318825","title":"\"Replication package for: Job applications and labor market flows\"","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Table (database); Job loss; Raw data; Code (set theory); Key (lock); Work (physics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01148207,0.003012384,0.002569065,0.002978368,0.001756149,0.003189982,0.005895413,0.001541924,0.5363241],"category_scores_gemma":[0.05567104,0.002907479,0.003741226,0.005079957,0.0008186986,0.002605898,0.004314892,0.0043086,0.3250547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001309673,"about_ca_system_score_gemma":0.00545291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008321766,"about_ca_topic_score_gemma":0.007627213,"domain_scores_codex":[0.9924689,0.002940959,0.0008569567,0.001612445,0.001402259,0.0007185334],"domain_scores_gemma":[0.9650913,0.01618877,0.001337367,0.0110509,0.005338627,0.0009930213],"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":[0.0003301548,0.00005531503,0.0005455581,0.0006022716,0.000145181,0.00002610685,0.0001143099,0.0004845503,0.0003585988,0.002569758,0.976112,0.0186563],"study_design_scores_gemma":[0.00116095,0.00009630532,0.005356931,0.0003107256,0.0001841031,0.00008726304,0.00008362939,0.002848439,0.002337979,0.01300274,0.9743443,0.000186726],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.001395279,0.0001204075,0.08486846,0.0008044509,0.001546216,0.001238003,0.7861353,0.1120261,0.01186581],"genre_scores_gemma":[0.01293242,0.0002351802,0.1736884,0.0009970561,0.000588643,0.01706933,0.5773093,0.1817631,0.03541664],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5363241,"threshold_uncertainty_score":0.6613773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0838603514230187,"score_gpt":0.3403235273414144,"score_spread":0.2564631759183957,"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."}}