{"id":"W6924971079","doi":"10.17605/osf.io/jshg7","title":"Reviewer selection biases editorial decisions on manuscripts","year":2017,"lang":"en","type":"other","venue":"Open Science Framework","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Reliability (semiconductor); MEDLINE; Peer review; Editorial board; Letter to the editor; Associate editor","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002132817,0.0002855636,0.0007431605,0.0005742915,0.001000477,0.001834262,0.00386644,0.0003360194,0.01923488],"category_scores_gemma":[0.01299601,0.0002840463,0.0001352128,0.0004538425,0.0006985505,0.0005151302,0.001066936,0.000380559,0.05646592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002065681,"about_ca_system_score_gemma":0.000134529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006930701,"about_ca_topic_score_gemma":0.00008280746,"domain_scores_codex":[0.9975368,0.00001163512,0.0003993941,0.001375192,0.0001711103,0.0005058368],"domain_scores_gemma":[0.9971768,0.0001338557,0.0009065319,0.00148237,0.0001276175,0.0001728377],"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":[0.000005455361,0.0000381478,0.0001355624,0.000004290344,0.0000210208,8.6265e-7,0.00003504007,0.000002870898,1.42888e-7,0.0266623,0.9710925,0.002001804],"study_design_scores_gemma":[0.0001406492,0.00005051725,0.0001036389,0.0008762343,0.000007400744,3.903896e-7,0.00002150093,0.00002039501,0.000002567903,0.006066519,0.9923565,0.0003536505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000005248902,0.0008411552,0.0001312672,0.000104968,0.2291033,0.0004417389,0.0003672321,0.00005379258,0.7689513],"genre_scores_gemma":[0.0001096607,0.00188449,0.002428462,0.0003131922,0.0207908,0.00005751431,0.000008098123,0.00009692298,0.9743109],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2083125,"threshold_uncertainty_score":0.9999612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1437797070050467,"score_gpt":0.329156877795428,"score_spread":0.1853771707903813,"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."}}