{"id":"W1628131229","doi":"10.1111/caje.12077","title":"Incentives for Journal Editors","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Incentive; Selection (genetic algorithm); Citation; Computer science; Test (biology); Positive economics; Library science; Data science; Economics; Artificial intelligence; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0153085,0.0004706095,0.0006236634,0.001979978,0.002064189,0.007300649,0.000914659,0.002675177,0.02869628],"category_scores_gemma":[0.1478832,0.0004501124,0.0003881181,0.001177663,0.0008742531,0.003299401,0.002265028,0.001396061,0.005352405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001676716,"about_ca_system_score_gemma":0.00273311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004942463,"about_ca_topic_score_gemma":0.0007241633,"domain_scores_codex":[0.9847882,0.007376358,0.001271483,0.001409214,0.003687375,0.00146733],"domain_scores_gemma":[0.7502595,0.1464194,0.05272214,0.009513753,0.01993975,0.02114557],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003076249,0.001882416,0.4420876,0.002417741,0.0005755829,0.002516401,0.008977706,0.004733594,0.01488812,0.1429181,0.1081497,0.2677768],"study_design_scores_gemma":[0.001761383,0.001899309,0.3451604,0.0007477901,0.0006624528,0.004550411,0.01293338,0.01807756,0.01555449,0.1740249,0.4243054,0.0003224703],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6503736,0.005084463,0.01046896,0.03170066,0.002397389,0.0005260652,0.0005259975,0.0005377566,0.2983852],"genre_scores_gemma":[0.9668925,0.0005119399,0.002243241,0.001951675,0.001377344,0.0001383412,0.00006979011,0.00003588703,0.02677914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9846915,"threshold_uncertainty_score":0.09599859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6173384028673773,"score_gpt":0.3755369723383634,"score_spread":0.2418014305290139,"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."}}