{"id":"W6921483030","doi":"10.7910/dvn/g3wbu7","title":"Replication Data for: 'Land Security and Mobility Frictions'","year":2024,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; York University","funders":"","keywords":"Replication (statistics); Replicate; Data security; Data file; Confidentiality; Data access","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002227157,0.0005242305,0.0005366287,0.0003054664,0.0002724233,0.0004044807,0.001934886,0.000477135,0.005192141],"category_scores_gemma":[0.002321265,0.0005302039,0.00008937963,0.0003802827,0.000228345,0.001014587,0.003276375,0.0007145912,0.4297788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002217141,"about_ca_system_score_gemma":0.0002428421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001087073,"about_ca_topic_score_gemma":0.002356906,"domain_scores_codex":[0.9955378,0.0001547726,0.0006077798,0.002813272,0.0004526448,0.0004337408],"domain_scores_gemma":[0.9818106,0.0002837981,0.0003128826,0.01719824,0.0001573538,0.0002370812],"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":[0.0001129267,0.0002035399,0.0000277342,0.0009997629,0.0001913802,0.00001364692,0.00002177067,6.955563e-7,0.00001318881,0.00003163969,0.9982813,0.0001024193],"study_design_scores_gemma":[0.0004842525,0.00004461178,0.00005535115,0.0001180816,0.001099082,0.00005264378,0.00004669666,0.001170975,0.000005592068,0.0006722313,0.9957381,0.0005123377],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005519028,0.00001370525,0.00004085657,0.00001005861,0.0007566112,0.001661747,0.9970971,0.0003038228,0.00006089732],"genre_scores_gemma":[0.00002016595,0.000617382,0.0004152458,0.00007940015,0.0005387993,0.0002917006,0.9978749,0.00009978464,0.00006269257],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4245867,"threshold_uncertainty_score":0.999715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0386338960774834,"score_gpt":0.3122774526775677,"score_spread":0.2736435566000843,"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."}}