{"id":"W2985242674","doi":"10.15185/izawol.467","title":"Transparency in empirical economic research","year":2019,"lang":"en","type":"article","venue":"IZA World of Labor","topic":"Data Analysis with R","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Transparency (behavior); Accounting; Business; Computer science; Computer security","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008145813,0.00007054326,0.0002117573,0.0005532952,0.00001705782,0.00004738269,0.001276532,0.00002692149,0.0002984978],"category_scores_gemma":[0.00002333918,0.00006533881,0.00004149326,0.001350022,0.00004473384,0.0003820724,0.0001591799,0.0001814761,0.0008504507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006944355,"about_ca_system_score_gemma":0.0001669912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002149352,"about_ca_topic_score_gemma":0.002286712,"domain_scores_codex":[0.9986649,0.0001315139,0.0003019075,0.000357928,0.0002635806,0.0002802424],"domain_scores_gemma":[0.9987904,0.0002055324,0.00004637929,0.0008416247,0.00005592247,0.00006010975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002395606,0.0001867696,0.8615078,0.00004558682,0.00003119927,0.00002439033,0.001257578,0.0006841275,0.001042636,0.1145001,0.0129564,0.007739436],"study_design_scores_gemma":[0.002044098,0.0002669466,0.7473707,0.0001875669,0.00001316625,0.000003619328,0.0001191055,0.05331281,0.01044568,0.01776883,0.1678397,0.0006277286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9733359,0.0002393476,0.001564765,0.005880207,0.0002794798,0.0002242392,0.00002645031,0.00004670882,0.01840286],"genre_scores_gemma":[0.9939268,0.00001264674,0.004013121,0.0001295819,0.00002466016,0.000006341952,0.000003830912,0.000005883533,0.001877198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1548833,"threshold_uncertainty_score":0.9999275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08210723770230255,"score_gpt":0.4067504289658305,"score_spread":0.3246431912635279,"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."}}