{"id":"W6889041981","doi":"10.25397/eur.21701702.v1","title":"Panel data-set of the paper Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Panel data; Containment (computer programming); Vulnerability (computing); Psychological intervention; Public policy; Panel Study of Income Dynamics; Panel analysis","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":[0.005394634,0.000672104,0.001291141,0.002124341,0.0007891937,0.002215484,0.002054181,0.00223642,0.1802129],"category_scores_gemma":[0.05548347,0.0007615896,0.001333794,0.004667111,0.0003043639,0.001262412,0.001586631,0.002998227,0.07307435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001175051,"about_ca_system_score_gemma":0.00337746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01716885,"about_ca_topic_score_gemma":0.0138035,"domain_scores_codex":[0.9952586,0.00145102,0.0009306012,0.0007862082,0.001245358,0.0003281427],"domain_scores_gemma":[0.9539878,0.01786249,0.006939309,0.007494694,0.01269418,0.001021457],"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":[0.0001415561,0.00004124625,0.004160073,0.0007803001,0.00008515531,0.00003424525,0.00005377617,0.0004328657,0.00008276551,0.002472792,0.9838759,0.007839131],"study_design_scores_gemma":[0.0005289216,0.00007538328,0.04540243,0.001282207,0.0001574329,0.0001017992,0.0002524163,0.0005761783,0.0005103055,0.003436434,0.947591,0.0000854009],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008370757,0.0002166949,0.001256048,0.0008687562,0.0003131263,0.0006064912,0.9895542,0.0001790112,0.006168631],"genre_scores_gemma":[0.0112201,0.0003615406,0.004347925,0.001221541,0.0002803886,0.006244804,0.9629402,0.0002538168,0.01312967],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1802129,"threshold_uncertainty_score":0.6028721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1906090403471878,"score_gpt":0.3819427406665483,"score_spread":0.1913337003193605,"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."}}