{"id":"W6950505058","doi":"10.5683/sp3/eqoykw","title":"Institutional Trust in the World 1995-2022: Data files and info - world","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Data file; Respondent; Identifier; File format; Flat file database; File sharing","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":[],"consensus_categories":[],"category_scores_codex":[0.0002026117,0.0002601238,0.0002185487,0.0003547249,0.00007467879,0.0001431751,0.0007500661,0.0000706204,0.0001229003],"category_scores_gemma":[0.00004863751,0.0002049205,0.00002938014,0.0004886246,0.0001075357,0.0002929985,0.0002801515,0.0007389532,0.0000466705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006352727,"about_ca_system_score_gemma":0.00004756137,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002567694,"about_ca_topic_score_gemma":0.1303452,"domain_scores_codex":[0.9989544,0.00002160501,0.0002563011,0.0002967403,0.0002307122,0.0002402008],"domain_scores_gemma":[0.9988883,0.0001309655,0.00002807005,0.0008994252,0.000007799978,0.00004545134],"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":[0.000003480473,0.000008875129,0.00001190181,0.0002162165,0.00002996394,0.0001184544,0.00004542555,0.0009102355,5.83925e-7,0.0005730157,0.9960489,0.002032923],"study_design_scores_gemma":[0.0001058025,0.000002579361,0.0003069482,0.0002566674,0.00005195432,0.00002244993,0.00004516335,0.001053768,0.000001807132,0.0003362161,0.9975786,0.0002380873],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000576674,0.003559728,0.0000323495,0.0002060994,0.0003782947,0.000142782,0.9904268,0.00008671725,0.005161446],"genre_scores_gemma":[0.0000568549,0.0009216677,0.0001926467,0.0003052762,0.0005895079,0.0000462188,0.9976897,0.00002218992,0.0001759966],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1277775,"threshold_uncertainty_score":0.8855237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01963514552337692,"score_gpt":0.2671884877900215,"score_spread":0.2475533422666446,"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."}}