{"id":"W6894097415","doi":"10.5281/zenodo.7293838","title":"A template README for social science replication packages","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Université du Québec à Montréal","funders":"","keywords":"Replication (statistics); Workflow; Code (set theory); File format; Research data","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":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.01468379,0.00008845283,0.0001179026,0.0005950499,0.0127393,0.002666311,0.003621109,0.00001617977,0.006417291],"category_scores_gemma":[0.006174799,0.00008650473,0.00006123132,0.002650832,0.0003204153,0.0004003244,0.004815902,0.0001487594,0.002111479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002036916,"about_ca_system_score_gemma":0.00001044664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006533751,"about_ca_topic_score_gemma":7.906685e-8,"domain_scores_codex":[0.9960622,0.0003534333,0.0003768246,0.001112617,0.001716402,0.000378482],"domain_scores_gemma":[0.9972533,0.0001236447,0.0002239367,0.001351241,0.0009324008,0.0001154897],"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":[0.00003633799,0.00006826733,0.000003871138,0.000005129466,0.000005205733,0.000001574372,0.00112974,0.00008589959,0.002724988,0.01838311,0.696128,0.2814279],"study_design_scores_gemma":[0.0002439181,0.0001229881,0.0009544739,0.000001704202,0.000005068532,0.00002270903,0.001458174,0.002849666,0.000198752,0.003621736,0.9904127,0.0001081007],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1354668,0.00009101812,0.1925417,0.01971987,0.00255153,0.003729224,0.003268871,0.003206845,0.6394241],"genre_scores_gemma":[0.9924753,0.000001691674,0.0006759361,0.0002675574,0.0001309416,3.077683e-7,0.0007193817,0.0002824008,0.005446505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8570085,"threshold_uncertainty_score":0.9986655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2089632388069236,"score_gpt":0.3829298306417269,"score_spread":0.1739665918348033,"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."}}