{"id":"W2952431389","doi":"10.1108/jices-06-2018-0059","title":"How hyped media and misleading editorials can influence impressions about Beall’s lists of “predatory” publications","year":2019,"lang":"en","type":"article","venue":"Journal of Information Communication and Ethics in Society","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Publishing; Originality; Value (mathematics); Deception; Impact factor; Scientific publishing; Library science; Computer science; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.02879041,0.00008317404,0.0002754374,0.004695624,0.0002364975,0.00144479,0.001284327,0.0002795172,0.0000277174],"category_scores_gemma":[0.05441743,0.00006187434,0.00008983593,0.01245334,0.0002890449,0.003506456,0.0004775967,0.0011116,0.000002634232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008427499,"about_ca_system_score_gemma":0.0004681203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003992653,"about_ca_topic_score_gemma":0.00002406197,"domain_scores_codex":[0.9951102,0.0003527829,0.001179415,0.0001007357,0.003091978,0.0001648753],"domain_scores_gemma":[0.9795012,0.0109566,0.001610294,0.0006033548,0.007118974,0.0002095693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009680038,0.0003234741,0.5515417,0.0004108832,0.0001407929,3.223037e-7,0.2024163,0.001160385,0.008019672,0.06039451,0.09235715,0.08313802],"study_design_scores_gemma":[0.002424844,0.0001479426,0.708376,0.0003497642,0.00001810371,0.0000217322,0.04064011,0.01123409,0.0008211095,0.02428799,0.2113588,0.0003195896],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686167,0.001379233,0.00135416,0.0258785,0.000855616,0.0002558547,0.00005736921,0.000008781448,0.001593838],"genre_scores_gemma":[0.9855638,0.009136564,0.004809161,0.0003306485,0.00006469386,0.000002963008,0.000007634993,0.00000294531,0.00008161515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1617762,"threshold_uncertainty_score":0.9995918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.393520143079422,"score_gpt":0.5364223676103,"score_spread":0.1429022245308781,"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."}}