{"id":"W2949716378","doi":"10.1098/rsos.171511","title":"Modelling science trustworthiness under publish or perish pressure","year":2018,"lang":"en","type":"article","venue":"Royal Society Open Science","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":229,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Trustworthiness; Incentive; Publication; Publish or perish; Public trust; Psychology; Political science; Public relations; Publishing; Social psychology; Economics; Law","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":["metaresearch","bibliometrics","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["metaresearch","sts","open_science"],"category_scores_codex":[0.08995748,0.0003042888,0.0004931157,0.009694794,0.006012098,0.05358576,0.03589765,0.0001636685,0.003453437],"category_scores_gemma":[0.02375905,0.0001906756,0.0002221343,0.3258646,0.01109209,0.009578385,0.01411442,0.0005223866,0.0005114988],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003596735,"about_ca_system_score_gemma":0.005973829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00108714,"about_ca_topic_score_gemma":0.00004504865,"domain_scores_codex":[0.9702885,0.0001266646,0.0008828108,0.002926202,0.02367641,0.002099379],"domain_scores_gemma":[0.9782463,0.001460538,0.0004250312,0.002432483,0.01591597,0.001519734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003536599,0.001480925,0.09236371,0.00004253366,0.0001051667,0.00002895007,0.01256611,0.1539563,0.004752759,0.03962716,0.4786527,0.21607],"study_design_scores_gemma":[0.0004550198,0.0002030686,0.01472421,0.00001381728,0.000007915317,0.000007893514,0.002416788,0.92058,0.001041787,0.005104573,0.05503347,0.0004114106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.626101,0.0004472281,0.2194656,0.004853545,0.004450196,0.001787958,0.00006949239,0.0001721897,0.1426528],"genre_scores_gemma":[0.9472345,0.00003261175,0.01960422,0.0009659164,0.0003003141,0.00002387672,9.090196e-7,0.0000173741,0.03182033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7666237,"threshold_uncertainty_score":0.9996614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5007204611956686,"score_gpt":0.557571533408018,"score_spread":0.05685107221234942,"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."}}