{"id":"W4398390286","doi":"10.7910/dvn/av0cmj","title":"Replication Data for: The Global Resonance of Human Rights: What Google Trends Can Tell Us","year":2022,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Global Security and Public Health","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Replication (statistics); Computer science; Internet privacy; Political science; Biology; Virology","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":[],"consensus_categories":[],"category_scores_codex":[0.002631815,0.0009769878,0.0009863329,0.006539178,0.001073214,0.004809127,0.001824254,0.002047517,0.1265759],"category_scores_gemma":[0.03258454,0.0005833583,0.001146987,0.01388846,0.0007082205,0.002665197,0.002797077,0.001970793,0.1004298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002025649,"about_ca_system_score_gemma":0.003945124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05399025,"about_ca_topic_score_gemma":0.0880652,"domain_scores_codex":[0.9974664,0.0004831638,0.0004077776,0.0004016275,0.0009269295,0.0003141861],"domain_scores_gemma":[0.9873224,0.004138642,0.00155746,0.002659738,0.003633237,0.0006885259],"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":[0.00003017171,0.000007543495,0.0009207782,0.0006571674,0.00001837905,0.00001877162,0.00004614178,0.00006727216,0.00003064296,0.0008548345,0.9954231,0.001925183],"study_design_scores_gemma":[0.0002322756,0.00001298484,0.00826003,0.0005903972,0.00002982872,0.00005495903,0.000283434,0.0002329329,0.0001613376,0.001630334,0.9884791,0.00003249396],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002594107,0.0001382117,0.00004922189,0.0005864463,0.00007912493,0.00002702397,0.9966832,0.0001715377,0.002005903],"genre_scores_gemma":[0.002426389,0.0002046808,0.0003922886,0.0002943474,0.00006004655,0.0003375601,0.9925225,0.0002137954,0.003548221],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1265759,"threshold_uncertainty_score":0.4234387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05928543750452452,"score_gpt":0.3637179483533404,"score_spread":0.3044325108488158,"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."}}